modelId stringlengths 4 111 | lastModified stringlengths 24 24 | tags list | pipeline_tag stringlengths 5 30 ⌀ | author stringlengths 2 34 ⌀ | config null | securityStatus null | id stringlengths 4 111 | likes int64 0 9.53k | downloads int64 2 73.6M | library_name stringlengths 2 84 ⌀ | created timestamp[us] | card stringlengths 101 901k | card_len int64 101 901k | embeddings list |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
vicgalle/xlm-roberta-large-xnli-anli | 2023-03-21T09:06:49.000Z | [
"transformers",
"pytorch",
"safetensors",
"xlm-roberta",
"text-classification",
"zero-shot-classification",
"nli",
"multilingual",
"dataset:mnli",
"dataset:xnli",
"dataset:anli",
"doi:10.57967/hf/0977",
"license:mit",
"endpoints_compatible",
"has_space",
"region:us"
] | zero-shot-classification | vicgalle | null | null | vicgalle/xlm-roberta-large-xnli-anli | 22 | 25,302 | transformers | 2022-03-02T23:29:05 | ---
language: multilingual
tags:
- zero-shot-classification
- nli
- pytorch
datasets:
- mnli
- xnli
- anli
license: mit
pipeline_tag: zero-shot-classification
widget:
- text: "De pugna erat fantastic. Nam Crixo decem quam dilexit et praeciderunt caput aemulus."
candidate_labels: "violent, peaceful"
- text: "La pelícu... | 1,751 | [
[
-0.01168060302734375,
-0.00994110107421875,
0.022003173828125,
0.0013093948364257812,
0.0057830810546875,
-0.0067138671875,
-0.00653839111328125,
-0.0131988525390625,
0.00817108154296875,
0.033172607421875,
-0.033843994140625,
-0.06561279296875,
-0.0475463867187... |
lllyasviel/control_v11p_sd15_openpose | 2023-08-04T08:24:23.000Z | [
"diffusers",
"art",
"controlnet",
"stable-diffusion",
"controlnet-v1-1",
"image-to-image",
"arxiv:2302.05543",
"license:openrail",
"has_space",
"diffusers:ControlNetModel",
"region:us"
] | image-to-image | lllyasviel | null | null | lllyasviel/control_v11p_sd15_openpose | 37 | 25,263 | diffusers | 2023-04-14T19:25:32 | ---
license: openrail
base_model: runwayml/stable-diffusion-v1-5
tags:
- art
- controlnet
- stable-diffusion
- controlnet-v1-1
- image-to-image
duplicated_from: ControlNet-1-1-preview/control_v11p_sd15_openpose
---
# Controlnet - v1.1 - *openpose Version*
**Controlnet v1.1** is the successor model of [Controlnet v1.0... | 15,683 | [
[
-0.0450439453125,
-0.04327392578125,
0.00942230224609375,
0.04217529296875,
-0.0170745849609375,
-0.0214996337890625,
0.0027980804443359375,
-0.04058837890625,
0.0396728515625,
0.0222320556640625,
-0.0555419921875,
-0.026947021484375,
-0.05462646484375,
-0.0... |
aipicasso/emi | 2023-09-26T21:36:30.000Z | [
"diffusers",
"stable-diffusion",
"text-to-image",
"arxiv:2307.01952",
"arxiv:2212.03860",
"license:openrail++",
"has_space",
"diffusers:StableDiffusionXLPipeline",
"region:us"
] | text-to-image | aipicasso | null | null | aipicasso/emi | 77 | 25,263 | diffusers | 2023-09-24T05:29:37 | ---
extra_gated_prompt: このモデルをこのページからダウンロードするためにはHugging Faceに登録された情報を提供する必要があります。この提供された情報は画像生成AIを活用する情報を案内するために使われます。 To download this model from this page, you need to provide information registered with Hugging Face. The information provided will be used to guide you on how to utilize the image-generation AI.
licen... | 6,690 | [
[
-0.04132080078125,
-0.061279296875,
0.031768798828125,
0.0162506103515625,
-0.03668212890625,
-0.005641937255859375,
0.0037021636962890625,
-0.0247955322265625,
0.041168212890625,
0.00567626953125,
-0.04437255859375,
-0.05078125,
-0.04083251953125,
0.0001533... |
PygmalionAI/pygmalion-6b | 2023-01-13T17:53:49.000Z | [
"transformers",
"pytorch",
"tensorboard",
"gptj",
"text-generation",
"text generation",
"conversational",
"en",
"license:creativeml-openrail-m",
"has_space",
"region:us"
] | conversational | PygmalionAI | null | null | PygmalionAI/pygmalion-6b | 700 | 25,223 | transformers | 2023-01-07T18:43:33 | ---
license: creativeml-openrail-m
language:
- en
thumbnail:
tags:
- text generation
- conversational
inference: false
---
# Pygmalion 6B
## Model description
Pymalion 6B is a proof-of-concept dialogue model based on EleutherAI's [GPT-J-6B](https://huggingface.co/EleutherAI/gpt-j-6B).
**Warning:** This model is **N... | 2,331 | [
[
-0.018585205078125,
-0.0648193359375,
0.0250244140625,
0.005687713623046875,
-0.03533935546875,
-0.02178955078125,
0.0009975433349609375,
-0.031829833984375,
0.01276397705078125,
0.035736083984375,
-0.0634765625,
-0.0265960693359375,
-0.037506103515625,
-0.0... |
MoritzLaurer/deberta-v3-large-zeroshot-v1 | 2023-10-13T07:43:53.000Z | [
"transformers",
"pytorch",
"deberta-v2",
"text-classification",
"zero-shot-classification",
"en",
"license:mit",
"endpoints_compatible",
"region:us"
] | zero-shot-classification | MoritzLaurer | null | null | MoritzLaurer/deberta-v3-large-zeroshot-v1 | 13 | 25,180 | transformers | 2023-10-03T03:24:13 | ---
language:
- en
tags:
- text-classification
- zero-shot-classification
pipeline_tag: zero-shot-classification
library_name: transformers
license: mit
---
# deberta-v3-large-zeroshot-v1
## Model description
The model is designed for zero-shot classification with the Hugging Face pipeline.
The model should be substa... | 4,326 | [
[
-0.0198822021484375,
-0.047760009765625,
0.032012939453125,
0.00957489013671875,
-0.0043182373046875,
-0.0126800537109375,
0.005290985107421875,
-0.048980712890625,
0.0221710205078125,
0.03607177734375,
-0.04266357421875,
-0.053314208984375,
-0.06195068359375,
... |
sentence-transformers/allenai-specter | 2022-06-15T21:31:20.000Z | [
"sentence-transformers",
"pytorch",
"tf",
"bert",
"feature-extraction",
"sentence-similarity",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | sentence-similarity | sentence-transformers | null | null | sentence-transformers/allenai-specter | 7 | 25,067 | sentence-transformers | 2022-03-02T23:29:05 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
license: apache-2.0
---
# allenai-specter
This model is a conversion of the [AllenAI SPECTER](https://github.com/allenai/specter) model to [sentence-transformers](https://www.SBERT.net). It can be used to ma... | 2,709 | [
[
-0.0247955322265625,
-0.044097900390625,
0.0199127197265625,
0.017486572265625,
-0.018646240234375,
-0.014984130859375,
-0.018280029296875,
-0.0199737548828125,
0.025634765625,
0.0272674560546875,
-0.0341796875,
-0.0274810791015625,
-0.052276611328125,
0.015... |
Sigma/financial-sentiment-analysis | 2022-05-14T11:48:56.000Z | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"text-classification",
"generated_from_trainer",
"dataset:financial_phrasebank",
"model-index",
"endpoints_compatible",
"region:us"
] | text-classification | Sigma | null | null | Sigma/financial-sentiment-analysis | 8 | 24,929 | transformers | 2022-05-14T08:41:10 | ---
tags:
- generated_from_trainer
datasets:
- financial_phrasebank
metrics:
- accuracy
- f1
model-index:
- name: financial-sentiment-analysis
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: financial_phrasebank
type: financial_phrasebank
args: s... | 1,555 | [
[
-0.033721923828125,
-0.048095703125,
0.005100250244140625,
0.0328369140625,
-0.0307769775390625,
-0.01062774658203125,
-0.0097808837890625,
-0.0041656494140625,
0.0142669677734375,
0.0286102294921875,
-0.0518798828125,
-0.062042236328125,
-0.053741455078125,
... |
keremberke/yolov5m-license-plate | 2023-01-01T09:59:05.000Z | [
"yolov5",
"tensorboard",
"yolo",
"vision",
"object-detection",
"pytorch",
"dataset:keremberke/license-plate-object-detection",
"model-index",
"has_space",
"region:us"
] | object-detection | keremberke | null | null | keremberke/yolov5m-license-plate | 24 | 24,840 | yolov5 | 2023-01-01T06:01:39 |
---
tags:
- yolov5
- yolo
- vision
- object-detection
- pytorch
library_name: yolov5
library_version: 7.0.6
inference: false
datasets:
- keremberke/license-plate-object-detection
model-index:
- name: keremberke/yolov5m-license-plate
results:
- task:
type: object-detection
dataset:
type: kerembe... | 2,082 | [
[
-0.068115234375,
-0.027740478515625,
0.036163330078125,
-0.0200347900390625,
-0.028167724609375,
-0.0271148681640625,
0.00815582275390625,
-0.043975830078125,
0.0100860595703125,
0.024749755859375,
-0.04437255859375,
-0.0572509765625,
-0.032135009765625,
-0.... |
nitrosocke/mo-di-diffusion | 2023-05-16T09:23:30.000Z | [
"diffusers",
"stable-diffusion",
"text-to-image",
"license:creativeml-openrail-m",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | nitrosocke | null | null | nitrosocke/mo-di-diffusion | 911 | 24,822 | diffusers | 2022-10-27T19:56:48 | ---
license: creativeml-openrail-m
tags:
- stable-diffusion
- text-to-image
---
**Mo Di Diffusion**
This is the fine-tuned Stable Diffusion 1.5 model trained on screenshots from a popular animation studio.
Use the tokens **_modern disney style_** in your prompts for the effect.
**If you enjoy my work, please consider... | 3,666 | [
[
-0.047088623046875,
-0.05841064453125,
0.0231475830078125,
0.032806396484375,
-0.015106201171875,
-0.0186614990234375,
0.01248931884765625,
-0.024688720703125,
0.0243377685546875,
0.0289764404296875,
-0.04742431640625,
-0.03729248046875,
-0.054168701171875,
... |
navteca/ms-marco-MiniLM-L-6-v2 | 2022-03-16T09:36:49.000Z | [
"sentence-transformers",
"pytorch",
"jax",
"bert",
"text-classification",
"en",
"license:mit",
"region:us"
] | text-classification | navteca | null | null | navteca/ms-marco-MiniLM-L-6-v2 | 2 | 24,729 | sentence-transformers | 2022-03-16T09:26:53 | ---
language: en
license: mit
pipeline_tag: text-classification
tags:
- sentence-transformers
---
# Cross-Encoder for MS Marco
The model can be used for Information Retrieval: Given a query, encode the query will all possible passages (e.g. retrieved with ElasticSearch). Then sort the passages in a decreasing order. ... | 2,597 | [
[
-0.033172607421875,
-0.0443115234375,
0.024749755859375,
0.0080108642578125,
-0.0152587890625,
0.0112152099609375,
-0.01444244384765625,
-0.042755126953125,
0.0266876220703125,
0.035552978515625,
-0.046173095703125,
-0.045654296875,
-0.05999755859375,
0.0068... |
ufal/robeczech-base | 2023-07-20T08:58:03.000Z | [
"transformers",
"pytorch",
"tf",
"safetensors",
"roberta",
"fill-mask",
"RobeCzech",
"Czech",
"RoBERTa",
"ÚFAL",
"cs",
"arxiv:2105.11314",
"license:cc-by-nc-sa-4.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | ufal | null | null | ufal/robeczech-base | 7 | 24,717 | transformers | 2022-03-02T23:29:05 |
---
language: cs
license: cc-by-nc-sa-4.0
tags:
- RobeCzech
- Czech
- RoBERTa
- ÚFAL
---
# Model Card for RobeCzech
**If you are having issues with the tokenizer, please see https://huggingface.co/ufal/robeczech-base/discussions/4#64b8f6a7f1f8e6ea5860b314.**
# Model Details
## Model Description
RobeCzech is a mon... | 5,380 | [
[
-0.033538818359375,
-0.04888916015625,
0.0220489501953125,
0.0153961181640625,
-0.02398681640625,
-0.021484375,
-0.0298919677734375,
-0.03375244140625,
0.007495880126953125,
0.01873779296875,
-0.042877197265625,
-0.051666259765625,
-0.049224853515625,
0.0078... |
bhadresh-savani/albert-base-v2-emotion | 2021-09-15T18:03:36.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"albert",
"text-classification",
"emotion",
"en",
"dataset:emotion",
"arxiv:1909.11942",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | text-classification | bhadresh-savani | null | null | bhadresh-savani/albert-base-v2-emotion | 0 | 24,543 | transformers | 2022-03-02T23:29:05 | ---
language:
- en
thumbnail: https://avatars3.githubusercontent.com/u/32437151?s=460&u=4ec59abc8d21d5feea3dab323d23a5860e6996a4&v=4
tags:
- text-classification
- emotion
- pytorch
license: apache-2.0
datasets:
- emotion
metrics:
- Accuracy, F1 Score
---
# Albert-base-v2-emotion
## Model description:
[Albert](https:/... | 2,634 | [
[
-0.029388427734375,
-0.03668212890625,
0.00896453857421875,
0.040802001953125,
-0.01050567626953125,
-0.0018453598022460938,
-0.0205230712890625,
-0.028778076171875,
0.0228729248046875,
0.0016994476318359375,
-0.04913330078125,
-0.04449462890625,
-0.048248291015... |
StanfordAIMI/stanford-deidentifier-base | 2022-11-23T19:44:40.000Z | [
"transformers",
"pytorch",
"bert",
"token-classification",
"sequence-tagger-model",
"pubmedbert",
"uncased",
"radiology",
"biomedical",
"en",
"dataset:radreports",
"license:mit",
"endpoints_compatible",
"has_space",
"region:us"
] | token-classification | StanfordAIMI | null | null | StanfordAIMI/stanford-deidentifier-base | 53 | 24,477 | transformers | 2022-06-16T18:24:42 | ---
widget:
- text: "PROCEDURE: Chest xray. COMPARISON: last seen on 1/1/2020 and also record dated of March 1st, 2019. FINDINGS: patchy airspace opacities. IMPRESSION: The results of the chest xray of January 1 2020 are the most concerning ones. The patient was transmitted to another service of UH Medical Center under... | 3,534 | [
[
-0.01338958740234375,
-0.0082550048828125,
0.049285888671875,
-0.0110626220703125,
-0.03173828125,
-0.01027679443359375,
0.0192413330078125,
-0.037139892578125,
0.0099945068359375,
0.009002685546875,
-0.02325439453125,
-0.046173095703125,
-0.057342529296875,
... |
TheBloke/Mistral-7B-Instruct-v0.1-GPTQ | 2023-09-29T20:48:48.000Z | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"finetuned",
"license:apache-2.0",
"text-generation-inference",
"region:us",
"has_space"
] | text-generation | TheBloke | null | null | TheBloke/Mistral-7B-Instruct-v0.1-GPTQ | 55 | 24,473 | transformers | 2023-09-28T22:34:03 | ---
base_model: mistralai/Mistral-7B-Instruct-v0.1
inference: false
license: apache-2.0
model_creator: Mistral AI
model_name: Mistral 7B Instruct v0.1
model_type: mistral
pipeline_tag: text-generation
prompt_template: '<s>[INST] {prompt} [/INST]'
quantized_by: TheBloke
tags:
- finetuned
---
<!-- header start -->
<!-- ... | 20,933 | [
[
-0.039581298828125,
-0.053619384765625,
0.01007080078125,
0.014434814453125,
-0.0158233642578125,
-0.0216064453125,
0.01021575927734375,
-0.03485107421875,
0.00893402099609375,
0.0264434814453125,
-0.041748046875,
-0.033355712890625,
-0.029754638671875,
-0.0... |
elyza/ELYZA-japanese-Llama-2-7b-instruct | 2023-08-29T03:46:15.000Z | [
"transformers",
"pytorch",
"llama",
"text-generation",
"ja",
"en",
"arxiv:2307.09288",
"license:llama2",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | elyza | null | null | elyza/ELYZA-japanese-Llama-2-7b-instruct | 39 | 24,421 | transformers | 2023-08-28T12:58:25 | ---
license: llama2
language:
- ja
- en
---
## ELYZA-japanese-Llama-2-7b
### Model Description
**ELYZA-japanese-Llama-2-7b** は、 Llama2をベースとして日本語能力を拡張するために追加事前学習を行ったモデルです。
詳細は [Blog記事](https://note.com/elyza/n/na405acaca130) を参照してください。
### Usage
```python
import tor... | 4,469 | [
[
-0.0343017578125,
-0.0467529296875,
0.0199127197265625,
0.026214599609375,
-0.04071044921875,
0.005817413330078125,
0.01020050048828125,
-0.046600341796875,
0.044830322265625,
0.0080413818359375,
-0.046356201171875,
-0.045318603515625,
-0.042816162109375,
0.... |
kykim/bert-kor-base | 2021-05-19T21:17:13.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"ko",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | kykim | null | null | kykim/bert-kor-base | 9 | 24,418 | transformers | 2022-03-02T23:29:05 | ---
language: ko
---
# Bert base model for Korean
* 70GB Korean text dataset and 42000 lower-cased subwords are used
* Check the model performance and other language models for Korean in [github](https://github.com/kiyoungkim1/LM-kor)
```python
from transformers import BertTokenizerFast, BertModel
tokenizer_bert = ... | 442 | [
[
-0.0102081298828125,
-0.0389404296875,
0.0206146240234375,
0.02374267578125,
-0.047119140625,
-0.003509521484375,
-0.03216552734375,
0.0018157958984375,
-0.0019130706787109375,
0.0404052734375,
-0.04156494140625,
-0.04205322265625,
-0.044403076171875,
0.0127... |
CAMeL-Lab/bert-base-arabic-camelbert-mix | 2021-09-14T14:34:32.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"Arabic",
"Dialect",
"Egyptian",
"Gulf",
"Levantine",
"Classical Arabic",
"MSA",
"Modern Standard Arabic",
"ar",
"arxiv:2103.06678",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | fill-mask | CAMeL-Lab | null | null | CAMeL-Lab/bert-base-arabic-camelbert-mix | 8 | 24,387 | transformers | 2022-03-02T23:29:04 | ---
language:
- ar
license: apache-2.0
tags:
- Arabic
- Dialect
- Egyptian
- Gulf
- Levantine
- Classical Arabic
- MSA
- Modern Standard Arabic
widget:
- text: "الهدف من الحياة هو [MASK] ."
---
# CAMeLBERT: A collection of pre-trained models for Arabic NLP tasks
## Model description
**CAMeLBERT** is a collection... | 11,113 | [
[
-0.03253173828125,
-0.04412841796875,
-0.005634307861328125,
0.02294921875,
-0.0296478271484375,
0.0081634521484375,
-0.01221466064453125,
-0.0283966064453125,
0.0322265625,
0.02667236328125,
-0.038177490234375,
-0.057769775390625,
-0.067626953125,
0.0082855... |
h2oai/h2ogpt-4096-llama2-7b-chat | 2023-08-24T18:35:05.000Z | [
"transformers",
"pytorch",
"safetensors",
"llama",
"text-generation",
"facebook",
"meta",
"llama-2",
"h2ogpt",
"en",
"license:llama2",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | h2oai | null | null | h2oai/h2ogpt-4096-llama2-7b-chat | 9 | 24,369 | transformers | 2023-08-09T17:18:42 | ---
inference: false
language:
- en
license: llama2
model_type: llama
pipeline_tag: text-generation
tags:
- facebook
- meta
- pytorch
- llama
- llama-2
- h2ogpt
---
h2oGPT clone of [Meta's Llama 2 7B Chat](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf).
Try it live on our [h2oGPT demo](https://gpt.h2o.ai) with... | 1,612 | [
[
-0.020233154296875,
-0.05181884765625,
0.035980224609375,
0.0377197265625,
-0.0296630859375,
0.0201263427734375,
0.003383636474609375,
-0.037261962890625,
0.032623291015625,
0.0196685791015625,
-0.02947998046875,
-0.048187255859375,
-0.050048828125,
-0.01922... |
google/pegasus-large | 2023-01-24T16:42:31.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"pegasus",
"text2text-generation",
"summarization",
"en",
"arxiv:1912.08777",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | summarization | google | null | null | google/pegasus-large | 70 | 24,250 | transformers | 2022-03-02T23:29:05 | ---
language: en
tags:
- summarization
---
### Pegasus Models
See Docs: [here](https://huggingface.co/transformers/master/model_doc/pegasus.html)
Original TF 1 code [here](https://github.com/google-research/pegasus)
Authors: Jingqing Zhang, Yao Zhao, Mohammad Saleh and Peter J. Liu on Dec 18, 2019
Maintained by: [@... | 3,332 | [
[
-0.0284271240234375,
-0.05816650390625,
0.0289306640625,
0.020721435546875,
-0.0264892578125,
-0.0250701904296875,
-0.0107269287109375,
-0.033721923828125,
0.0394287109375,
0.0221405029296875,
-0.058349609375,
-0.045867919921875,
-0.05474853515625,
-0.001397... |
timm/cait_m36_384.fb_dist_in1k | 2023-04-13T01:40:32.000Z | [
"timm",
"pytorch",
"safetensors",
"image-classification",
"dataset:imagenet-1k",
"arxiv:2103.17239",
"license:apache-2.0",
"region:us"
] | image-classification | timm | null | null | timm/cait_m36_384.fb_dist_in1k | 0 | 24,198 | timm | 2023-04-13T01:37:00 | ---
tags:
- image-classification
- timm
library_tag: timm
license: apache-2.0
datasets:
- imagenet-1k
---
# Model card for cait_m36_384.fb_dist_in1k
A CaiT (Class-Attention in Image Transformers) image classification model. Pretrained on ImageNet-1k with distillation by paper authors.
## Model Details
- **Model Type:... | 2,738 | [
[
-0.039825439453125,
-0.0282745361328125,
0.0030117034912109375,
0.020477294921875,
-0.030426025390625,
-0.02398681640625,
-0.00972747802734375,
-0.0198974609375,
0.01503753662109375,
0.0246124267578125,
-0.04571533203125,
-0.04449462890625,
-0.058441162109375,
... |
Intel/bert-base-uncased-mrpc | 2022-12-05T13:34:53.000Z | [
"transformers",
"pytorch",
"bert",
"text-classification",
"generated_from_trainer",
"en",
"dataset:glue",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | text-classification | Intel | null | null | Intel/bert-base-uncased-mrpc | 1 | 24,156 | transformers | 2022-04-06T07:30:07 | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bert-base-uncased-mrpc
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: GLUE MRPC
type: glue
args: mrpc
metric... | 3,599 | [
[
-0.037811279296875,
-0.040283203125,
0.0079193115234375,
0.01192474365234375,
-0.038604736328125,
-0.0248870849609375,
-0.023193359375,
-0.0179443359375,
0.021820068359375,
0.0207977294921875,
-0.052001953125,
-0.032318115234375,
-0.049407958984375,
-0.02415... |
Phind/Phind-CodeLlama-34B-v2 | 2023-08-28T21:43:01.000Z | [
"transformers",
"pytorch",
"llama",
"text-generation",
"code llama",
"license:llama2",
"model-index",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | Phind | null | null | Phind/Phind-CodeLlama-34B-v2 | 479 | 24,150 | transformers | 2023-08-28T21:29:09 | ---
license: llama2
model-index:
- name: Phind-CodeLlama-34B-v1
results:
- task:
type: text-generation
dataset:
type: openai_humaneval
name: HumanEval
metrics:
- name: pass@1
type: pass@1
value: 73.8%
verified: false
tags:
- code llama
---
# **Phind-CodeLlama-34B-v2*... | 3,745 | [
[
-0.02569580078125,
-0.054962158203125,
0.019195556640625,
0.0212554931640625,
-0.02825927734375,
-0.004123687744140625,
-0.00615692138671875,
-0.031768798828125,
-0.002338409423828125,
0.0259552001953125,
-0.037322998046875,
-0.054840087890625,
-0.02384948730468... |
The-Face-Of-Goonery/Huginn-13b-v1.2 | 2023-08-17T18:40:12.000Z | [
"transformers",
"pytorch",
"llama",
"text-generation",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | The-Face-Of-Goonery | null | null | The-Face-Of-Goonery/Huginn-13b-v1.2 | 10 | 24,107 | transformers | 2023-08-08T20:31:15 | ---
{}
---
better version of the old huginn model, I THINK it's a little tamer now? less of a schizophrenic loose cannon,
it's chronos, airoboros, hermes, beluga merged using my random-merge method, then merged with mythologic using model revolver, then merged with ledgerdemain, and the limarp lora.
I'm aware that ... | 1,053 | [
[
-0.0439453125,
-0.04595947265625,
0.018951416015625,
-0.0183868408203125,
-0.051361083984375,
-0.026092529296875,
-0.005725860595703125,
-0.073486328125,
0.055572509765625,
0.053375244140625,
-0.0335693359375,
-0.01065826416015625,
-0.03607177734375,
-0.0066... |
ml6team/distilbert-base-german-cased-toxic-comments | 2022-06-15T22:10:04.000Z | [
"transformers",
"pytorch",
"distilbert",
"text-classification",
"german",
"classification",
"de",
"dataset:germeval21",
"arxiv:1701.08118",
"endpoints_compatible",
"has_space",
"region:us"
] | text-classification | ml6team | null | null | ml6team/distilbert-base-german-cased-toxic-comments | 5 | 24,089 | transformers | 2022-03-02T23:29:05 | ---
language:
- de
tags:
- distilbert
- german
- classification
datasets:
- germeval21
widget:
- text: "Das ist ein guter Punkt, so hatte ich das noch nicht betrachtet."
example_title: "Agreement (non-toxic)"
- text: "Wow, was ein geiles Spiel. Glückwunsch."
example_title: "Football (non-toxic)"
- text: "Halt deine... | 3,969 | [
[
-0.019287109375,
-0.04669189453125,
0.0176849365234375,
0.014190673828125,
-0.01444244384765625,
-0.01531219482421875,
-0.00719451904296875,
-0.0306854248046875,
-0.00878143310546875,
0.00894927978515625,
-0.0390625,
-0.058990478515625,
-0.059814453125,
0.00... |
openlm-research/open_llama_3b | 2023-06-16T00:44:10.000Z | [
"transformers",
"pytorch",
"llama",
"text-generation",
"dataset:togethercomputer/RedPajama-Data-1T",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | openlm-research | null | null | openlm-research/open_llama_3b | 121 | 24,074 | transformers | 2023-06-07T09:06:48 | ---
license: apache-2.0
datasets:
- togethercomputer/RedPajama-Data-1T
---
# OpenLLaMA: An Open Reproduction of LLaMA
In this repo, we present a permissively licensed open source reproduction of Meta AI's [LLaMA](https://ai.facebook.com/blog/large-language-model-llama-meta-ai/) large language model. We are releasing... | 10,503 | [
[
-0.0233001708984375,
-0.0538330078125,
0.01861572265625,
0.030181884765625,
-0.0186767578125,
-0.0037174224853515625,
-0.0243682861328125,
-0.044158935546875,
0.0281219482421875,
0.0193023681640625,
-0.0299224853515625,
-0.05059814453125,
-0.049591064453125,
... |
danbrown/Lyriel-v1-5 | 2023-04-30T16:52:53.000Z | [
"diffusers",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"region:us"
] | null | danbrown | null | null | danbrown/Lyriel-v1-5 | 1 | 24,051 | diffusers | 2023-04-30T16:29:17 | Not official! This are diffusers weights for https://civitai.com/models/22922/lyriel
Based on Stable Diffusion v1.5 | 115 | [
[
-0.0127716064453125,
-0.0196075439453125,
0.030853271484375,
0.042877197265625,
-0.0046539306640625,
-0.0099334716796875,
0.0200958251953125,
-0.0218505859375,
0.04913330078125,
0.001476287841796875,
-0.041717529296875,
0.004924774169921875,
-0.0224761962890625,... |
llmrails/ember-v1 | 2023-10-22T03:23:08.000Z | [
"sentence-transformers",
"pytorch",
"safetensors",
"bert",
"mteb",
"feature-extraction",
"sentence-similarity",
"transformers",
"en",
"arxiv:2205.12035",
"arxiv:2209.11055",
"doi:10.57967/hf/1241",
"license:mit",
"model-index",
"endpoints_compatible",
"has_space",
"region:us"
] | feature-extraction | llmrails | null | null | llmrails/ember-v1 | 23 | 24,029 | sentence-transformers | 2023-10-10T15:56:42 | ---
tags:
- mteb
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
language: en
license: mit
model-index:
- name: ember_v1
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
co... | 66,227 | [
[
-0.0197601318359375,
-0.063720703125,
0.045928955078125,
0.0143585205078125,
-0.022308349609375,
-0.005390167236328125,
-0.01195526123046875,
-0.005008697509765625,
0.032257080078125,
0.011016845703125,
-0.041015625,
-0.0751953125,
-0.06451416015625,
0.00142... |
nferruz/ProtGPT2 | 2023-06-20T13:05:57.000Z | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | nferruz | null | null | nferruz/ProtGPT2 | 66 | 24,016 | transformers | 2022-03-07T12:29:07 | ---
license: apache-2.0
pipeline_tag: text-generation
widget:
- text: "<|endoftext|>"
inference:
parameters:
top_k: 950
repetition_penalty: 1.2
---
# **ProtGPT2**
ProtGPT2 ([peer-reviewed paper](https://www.nature.com/articles/s41467-022-32007-7)) is a language model that speaks the protein language and can... | 8,179 | [
[
-0.04022216796875,
-0.06591796875,
0.028076171875,
0.00441741943359375,
-0.03070068359375,
-0.0189056396484375,
0.0034275054931640625,
-0.02825927734375,
0.0300750732421875,
0.01218414306640625,
-0.04339599609375,
-0.0223236083984375,
-0.056640625,
0.0247344... |
sileod/deberta-v3-base-tasksource-nli | 2023-11-02T08:48:16.000Z | [
"transformers",
"pytorch",
"safetensors",
"deberta-v2",
"text-classification",
"deberta-v3-base",
"deberta-v3",
"deberta",
"nli",
"natural-language-inference",
"multitask",
"multi-task",
"pipeline",
"extreme-multi-task",
"extreme-mtl",
"tasksource",
"zero-shot",
"rlhf",
"zero-sho... | zero-shot-classification | sileod | null | null | sileod/deberta-v3-base-tasksource-nli | 80 | 24,004 | transformers | 2023-01-13T13:47:22 | ---
license: apache-2.0
language: en
tags:
- deberta-v3-base
- deberta-v3
- deberta
- text-classification
- nli
- natural-language-inference
- multitask
- multi-task
- pipeline
- extreme-multi-task
- extreme-mtl
- tasksource
- zero-shot
- rlhf
model-index:
- name: deberta-v3-base-tasksource-nli
results:
- task:
... | 9,757 | [
[
-0.01678466796875,
-0.03155517578125,
0.027862548828125,
0.016693115234375,
-0.01227569580078125,
-0.0199127197265625,
0.00797271728515625,
-0.0297088623046875,
-0.0029754638671875,
0.024566650390625,
-0.051483154296875,
-0.031280517578125,
-0.05084228515625,
... |
cardiffnlp/twitter-xlm-roberta-base | 2023-08-31T01:52:58.000Z | [
"transformers",
"pytorch",
"tf",
"xlm-roberta",
"fill-mask",
"multilingual",
"arxiv:2104.12250",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | cardiffnlp | null | null | cardiffnlp/twitter-xlm-roberta-base | 11 | 23,880 | transformers | 2022-03-02T23:29:05 | ---
language: multilingual
widget:
- text: "🤗🤗🤗<mask>"
- text: "🔥The goal of life is <mask> . 🔥"
- text: "Il segreto della vita è l’<mask> . ❤️"
- text: "Hasta <mask> 👋!"
---
# Twitter-XLM-Roberta-base
This is a XLM-Roberta-base model trained on ~198M multilingual tweets, described and evaluated in the [referen... | 3,386 | [
[
-0.0168609619140625,
-0.03997802734375,
0.0299835205078125,
0.032470703125,
-0.0272064208984375,
0.0204925537109375,
-0.03424072265625,
-0.0183868408203125,
0.03216552734375,
0.00307464599609375,
-0.044708251953125,
-0.07501220703125,
-0.051025390625,
0.0173... |
google/bigbird-roberta-base | 2021-06-02T14:30:54.000Z | [
"transformers",
"pytorch",
"jax",
"big_bird",
"pretraining",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"dataset:cc_news",
"arxiv:2007.14062",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | null | google | null | null | google/bigbird-roberta-base | 38 | 23,868 | transformers | 2022-03-02T23:29:05 | ---
language: en
license: apache-2.0
datasets:
- bookcorpus
- wikipedia
- cc_news
---
# BigBird base model
BigBird, is a sparse-attention based transformer which extends Transformer based models, such as BERT to much longer sequences. Moreover, BigBird comes along with a theoretical understanding of the capabilities ... | 2,851 | [
[
-0.0300750732421875,
-0.053009033203125,
0.00936126708984375,
0.01995849609375,
-0.0078277587890625,
-0.0187835693359375,
-0.0322265625,
-0.040863037109375,
0.018218994140625,
0.024169921875,
-0.04998779296875,
-0.01605224609375,
-0.0601806640625,
0.01063537... |
aubmindlab/bert-base-arabertv2 | 2023-08-03T12:32:06.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"fill-mask",
"ar",
"dataset:wikipedia",
"dataset:Osian",
"dataset:1.5B-Arabic-Corpus",
"dataset:oscar-arabic-unshuffled",
"arxiv:2003.00104",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | aubmindlab | null | null | aubmindlab/bert-base-arabertv2 | 13 | 23,813 | transformers | 2022-03-02T23:29:05 | ---
language: ar
datasets:
- wikipedia
- Osian
- 1.5B-Arabic-Corpus
- oscar-arabic-unshuffled
widget:
- text: " عاصم +ة لبنان هي [MASK] ."
---
# AraBERT v1 & v2 : Pre-training BERT for Arabic Language Understanding
<img src="https://raw.githubusercontent.com/aub-mind/arabert/master/arabert_logo.png" width="100" alig... | 8,276 | [
[
-0.0528564453125,
-0.053680419921875,
0.0246124267578125,
0.01044464111328125,
-0.024169921875,
-0.007049560546875,
-0.01032257080078125,
-0.043212890625,
0.0188140869140625,
0.0213165283203125,
-0.04376220703125,
-0.050384521484375,
-0.058990478515625,
0.00... |
nghuyong/ernie-3.0-base-zh | 2022-09-10T08:45:06.000Z | [
"transformers",
"pytorch",
"ernie",
"fill-mask",
"zh",
"arxiv:2107.02137",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | nghuyong | null | null | nghuyong/ernie-3.0-base-zh | 64 | 23,787 | transformers | 2022-08-22T07:54:44 | ---
language: zh
---
# ERNIE-3.0-base-zh
## Introduction
ERNIE 3.0: Large-scale Knowledge Enhanced Pre-training for Language Understanding and Generation
More detail: https://arxiv.org/abs/2107.02137
## Released Model Info
This released pytorch model is converted from the officially released PaddlePaddle ERNIE mod... | 1,282 | [
[
-0.0275115966796875,
-0.040679931640625,
0.00897216796875,
0.023223876953125,
-0.02569580078125,
-0.032623291015625,
-0.039886474609375,
-0.0325927734375,
0.00537109375,
0.0341796875,
-0.0300140380859375,
-0.029815673828125,
-0.04632568359375,
-0.01333618164... |
Yntec/edgeOfRealism | 2023-09-26T08:22:50.000Z | [
"diffusers",
"Photorealistic",
"Highly Detailed",
"Realistic",
"AreThoseLevel4Plates",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"license:creativeml-openrail-m",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | Yntec | null | null | Yntec/edgeOfRealism | 1 | 23,783 | diffusers | 2023-09-25T06:03:56 | ---
license: creativeml-openrail-m
library_name: diffusers
pipeline_tag: text-to-image
tags:
- Photorealistic
- Highly Detailed
- Realistic
- AreThoseLevel4Plates
- stable-diffusion
- stable-diffusion-diffusers
- diffusers
- text-to-image
---
# EdgeOfRealism
Original page: https://civitai.com/models/21813?modelVersi... | 759 | [
[
-0.031280517578125,
-0.06341552734375,
0.032318115234375,
0.0183563232421875,
-0.0189666748046875,
0.017913818359375,
0.040283203125,
-0.035186767578125,
0.0477294921875,
0.030731201171875,
-0.057769775390625,
-0.0657958984375,
-0.035430908203125,
-0.0310211... |
RinInori/bert-base-uncased_finetuned_sentiments | 2023-05-28T10:16:19.000Z | [
"transformers",
"pytorch",
"bert",
"text-classification",
"en",
"dataset:custom",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-classification | RinInori | null | null | RinInori/bert-base-uncased_finetuned_sentiments | 1 | 23,745 | transformers | 2023-05-09T04:18:25 | ---
language: en
license: apache-2.0
datasets:
- custom
task_categories:
- text-classification
task_ids:
- sentiment-classification
---
# BERT ForSequenceClassification Fine-tuned for Sentiment Analysis
This model is a fine-tuned version of the `BERT ForSequenceClassification` model for sentiment analysis.
It is tra... | 4,175 | [
[
-0.035308837890625,
-0.0362548828125,
0.01012420654296875,
0.0309600830078125,
-0.02606201171875,
0.00440216064453125,
-0.0098724365234375,
-0.0174102783203125,
0.0244903564453125,
0.0172576904296875,
-0.046417236328125,
-0.050689697265625,
-0.05084228515625,
... |
albert-xxlarge-v2 | 2023-04-06T13:40:06.000Z | [
"transformers",
"pytorch",
"tf",
"safetensors",
"albert",
"fill-mask",
"exbert",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | null | null | null | albert-xxlarge-v2 | 12 | 23,643 | transformers | 2022-03-02T23:29:04 | ---
tags:
- exbert
language: en
license: apache-2.0
datasets:
- bookcorpus
- wikipedia
---
# ALBERT XXLarge v2
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1909.11942) and first released in
[this repository](https://gith... | 9,940 | [
[
-0.0081634521484375,
-0.0367431640625,
0.0181884765625,
0.02392578125,
-0.031585693359375,
0.0010280609130859375,
0.00940704345703125,
-0.01422882080078125,
0.0264129638671875,
0.04595947265625,
-0.04266357421875,
-0.0328369140625,
-0.061737060546875,
0.0088... |
HuggingFaceM4/idefics-9b | 2023-10-12T18:45:40.000Z | [
"transformers",
"pytorch",
"safetensors",
"idefics",
"pretraining",
"multimodal",
"text",
"image",
"image-to-text",
"text-generation",
"en",
"dataset:HuggingFaceM4/OBELICS",
"dataset:wikipedia",
"dataset:facebook/pmd",
"dataset:laion/laion2B-en",
"arxiv:2303.12733",
"arxiv:2109.05014... | text-generation | HuggingFaceM4 | null | null | HuggingFaceM4/idefics-9b | 25 | 23,559 | transformers | 2023-07-11T17:47:40 | ---
language: en
tags:
- multimodal
- text
- image
- image-to-text
license: other
datasets:
- HuggingFaceM4/OBELICS
- wikipedia
- facebook/pmd
- laion/laion2B-en
pipeline_tag: text-generation
inference: false
---
<p align="center">
<img src="https://huggingface.co/HuggingFaceM4/idefics-80b/resolve/main/assets/IDEF... | 43,239 | [
[
-0.049896240234375,
-0.056732177734375,
0.018463134765625,
0.0288543701171875,
-0.0247802734375,
-0.003421783447265625,
-0.027557373046875,
-0.047332763671875,
0.003223419189453125,
0.0163421630859375,
-0.047271728515625,
-0.03759765625,
-0.047210693359375,
... |
Yntec/Thriller | 2023-10-07T03:02:34.000Z | [
"diffusers",
"General",
"Photo",
"Movie",
"LandScapes",
"MagicArt35",
"Lykon",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"license:creativeml-openrail-m",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | Yntec | null | null | Yntec/Thriller | 1 | 23,545 | diffusers | 2023-10-07T01:36:05 | ---
license: creativeml-openrail-m
library_name: diffusers
pipeline_tag: text-to-image
tags:
- General
- Photo
- Movie
- LandScapes
- MagicArt35
- Lykon
- stable-diffusion
- stable-diffusion-diffusers
- diffusers
- text-to-image
---
# Thriller
A mix of PhotoMovieXFinal and AbsoluteRemix.
![Comparison](https://cdn-... | 1,210 | [
[
-0.031158447265625,
-0.04705810546875,
0.0242462158203125,
0.0261993408203125,
-0.0167388916015625,
0.0247039794921875,
0.0279083251953125,
-0.041839599609375,
0.04412841796875,
0.0276031494140625,
-0.041290283203125,
-0.04913330078125,
-0.032196044921875,
-... |
nitrosocke/elden-ring-diffusion | 2023-05-16T09:21:07.000Z | [
"diffusers",
"stable-diffusion",
"text-to-image",
"license:creativeml-openrail-m",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | nitrosocke | null | null | nitrosocke/elden-ring-diffusion | 321 | 23,396 | diffusers | 2022-10-05T22:55:13 | ---
license: creativeml-openrail-m
tags:
- stable-diffusion
- text-to-image
---
**Elden Ring Diffusion**
This is the fine-tuned Stable Diffusion model trained on the game art from Elden Ring.
Use the tokens **_elden ring style_** in your prompts for the effect.
You can download the latest version here: [eldenRing-v3-... | 3,308 | [
[
-0.0364990234375,
-0.065673828125,
0.0165863037109375,
0.00797271728515625,
-0.0150146484375,
-0.01922607421875,
0.00844573974609375,
-0.04461669921875,
0.03271484375,
0.04803466796875,
-0.049163818359375,
-0.061370849609375,
-0.0360107421875,
-0.01145935058... |
Salesforce/codet5p-110m-embedding | 2023-07-18T10:44:11.000Z | [
"transformers",
"pytorch",
"codet5p_embedding",
"custom_code",
"arxiv:2305.07922",
"license:bsd-3-clause",
"endpoints_compatible",
"region:us"
] | null | Salesforce | null | null | Salesforce/codet5p-110m-embedding | 21 | 23,363 | transformers | 2023-07-18T09:52:49 | ---
license: bsd-3-clause
---
# CodeT5+ 110M Embedding Models
## Model description
[CodeT5+](https://github.com/salesforce/CodeT5/tree/main/CodeT5+) is a new family of open code large language models
with an encoder-decoder architecture that can flexibly operate in different modes (i.e. _encoder-only_, _decoder-only... | 6,852 | [
[
-0.039031982421875,
-0.037567138671875,
0.0179901123046875,
0.0067596435546875,
-0.01142120361328125,
0.00559234619140625,
-0.0146636962890625,
-0.0088043212890625,
0.032867431640625,
0.0192108154296875,
-0.0251007080078125,
-0.058868408203125,
-0.0374755859375,... |
SenseTime/deformable-detr | 2023-09-07T06:14:08.000Z | [
"transformers",
"pytorch",
"safetensors",
"deformable_detr",
"object-detection",
"vision",
"dataset:coco",
"arxiv:2010.04159",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | object-detection | SenseTime | null | null | SenseTime/deformable-detr | 10 | 23,346 | transformers | 2022-03-02T23:29:05 | ---
license: apache-2.0
tags:
- object-detection
- vision
datasets:
- coco
widget:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/savanna.jpg
example_title: Savanna
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/football-match.jpg
example_title: Football Match
- s... | 4,752 | [
[
-0.037078857421875,
-0.03387451171875,
0.0021495819091796875,
-0.0060577392578125,
-0.01959228515625,
-0.00699615478515625,
-0.003162384033203125,
-0.0526123046875,
0.01168060302734375,
0.01500701904296875,
-0.038604736328125,
-0.0440673828125,
-0.0482177734375,... |
FFusion/FFXL400 | 2023-09-13T21:57:32.000Z | [
"diffusers",
"safetensors",
"stable-diffusion-xl",
"stable-diffusion-xl-diffusers",
"stable-diffusion",
"text-to-image",
"ffai",
"en",
"doi:10.57967/hf/1095",
"license:openrail++",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionXLPipeline",
"region:us"
] | text-to-image | FFusion | null | null | FFusion/FFXL400 | 6 | 23,291 | diffusers | 2023-09-08T14:22:11 | ---
license: openrail++
base_model: FFusion/FFusionXL-BASE
tags:
- stable-diffusion-xl
- stable-diffusion-xl-diffusers
- stable-diffusion
- text-to-image
- diffusers
- ffai
inference: true
widget:
- text: >-
a dog in colorful exploding clouds, dreamlike surrealism colorful smoke and
fire coming out of it, explo... | 14,459 | [
[
-0.051361083984375,
-0.042572021484375,
0.01412200927734375,
0.0220489501953125,
-0.01256561279296875,
-0.0028247833251953125,
0.01922607421875,
-0.05401611328125,
0.03662109375,
0.0313720703125,
-0.060455322265625,
-0.0316162109375,
-0.042327880859375,
0.00... |
lmsys/vicuna-7b-v1.5-16k | 2023-10-10T05:31:20.000Z | [
"transformers",
"pytorch",
"llama",
"text-generation",
"arxiv:2307.09288",
"arxiv:2306.05685",
"license:llama2",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | lmsys | null | null | lmsys/vicuna-7b-v1.5-16k | 59 | 23,164 | transformers | 2023-07-31T22:03:06 | ---
inference: false
license: llama2
---
# Vicuna Model Card
## Model Details
Vicuna is a chat assistant trained by fine-tuning Llama 2 on user-shared conversations collected from ShareGPT.
- **Developed by:** [LMSYS](https://lmsys.org/)
- **Model type:** An auto-regressive language model based on the transformer a... | 2,071 | [
[
-0.0212554931640625,
-0.0655517578125,
0.029632568359375,
0.0239105224609375,
-0.045654296875,
-0.013763427734375,
-0.006175994873046875,
-0.0474853515625,
0.0212860107421875,
0.0247039794921875,
-0.0447998046875,
-0.04644775390625,
-0.038299560546875,
-0.00... |
HooshvareLab/bert-base-parsbert-uncased | 2021-05-18T20:47:21.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"arxiv:2005.12515",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | HooshvareLab | null | null | HooshvareLab/bert-base-parsbert-uncased | 18 | 23,123 | transformers | 2022-03-02T23:29:04 | ## ParsBERT: Transformer-based Model for Persian Language Understanding
ParsBERT is a monolingual language model based on Google’s BERT architecture with the same configurations as BERT-Base.
Paper presenting ParsBERT: [arXiv:2005.12515](https://arxiv.org/abs/2005.12515)
All the models (downstream tasks) are uncase... | 5,818 | [
[
-0.03900146484375,
-0.055328369140625,
0.01141357421875,
0.0277099609375,
-0.0261077880859375,
0.004695892333984375,
-0.0287322998046875,
-0.008514404296875,
0.0087738037109375,
0.011749267578125,
-0.035858154296875,
-0.051025390625,
-0.051666259765625,
-0.0... |
Voicelab/vlt5-base-keywords | 2023-08-16T07:34:41.000Z | [
"transformers",
"pytorch",
"safetensors",
"t5",
"text2text-generation",
"keywords-generation",
"text-classifiation",
"other",
"pl",
"en",
"dataset:posmac",
"arxiv:2209.14008",
"license:cc-by-4.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"text-generation-inference... | text2text-generation | Voicelab | null | null | Voicelab/vlt5-base-keywords | 35 | 23,118 | transformers | 2022-09-27T12:13:59 | ---
license: cc-by-4.0
language:
- pl
- en
datasets:
- posmac
pipeline_tag: text2text-generation
pipeline_kwargs:
- no_repeat_ngram_size=3
- num_beams=4
tags:
- keywords-generation
- text-classifiation
- other
widget:
- text: "Keywords: Our vlT5 model is a keyword generation model based on encoder-decoder architecture... | 11,196 | [
[
-0.036468505859375,
-0.034454345703125,
0.0276336669921875,
-0.0011138916015625,
-0.0206146240234375,
0.01270294189453125,
-0.00457000732421875,
-0.0137481689453125,
0.0236053466796875,
0.01226043701171875,
-0.037445068359375,
-0.0615234375,
-0.051666259765625,
... |
Helsinki-NLP/opus-mt-ROMANCE-en | 2023-08-16T11:25:14.000Z | [
"transformers",
"pytorch",
"tf",
"rust",
"marian",
"text2text-generation",
"translation",
"roa",
"en",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | translation | Helsinki-NLP | null | null | Helsinki-NLP/opus-mt-ROMANCE-en | 5 | 23,112 | transformers | 2022-03-02T23:29:04 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-ROMANCE-en
* source languages: fr,fr_BE,fr_CA,fr_FR,wa,frp,oc,ca,rm,lld,fur,lij,lmo,es,es_AR,es_CL,es_CO,es_CR,es_DO,es_EC,es_ES,es_GT,es_HN,es_MX,es_NI,es_PA,es_PE,es_PR,es_SV,es_UY,es_VE,pt,pt_br,pt_BR,pt_PT,gl,lad,an,mwl,it,it_IT,co,nap,scn,vec,sc,ro,la
*... | 2,155 | [
[
-0.0233917236328125,
-0.038543701171875,
0.017730712890625,
0.032928466796875,
-0.0250091552734375,
-0.0173492431640625,
-0.01617431640625,
-0.010986328125,
0.01267242431640625,
0.03277587890625,
-0.051971435546875,
-0.054046630859375,
-0.033447265625,
0.024... |
keremberke/yolov8s-table-extraction | 2023-02-22T13:02:55.000Z | [
"ultralytics",
"tensorboard",
"v8",
"ultralyticsplus",
"yolov8",
"yolo",
"vision",
"object-detection",
"pytorch",
"awesome-yolov8-models",
"dataset:keremberke/table-extraction",
"model-index",
"region:us"
] | object-detection | keremberke | null | null | keremberke/yolov8s-table-extraction | 13 | 23,060 | ultralytics | 2023-01-29T04:10:31 |
---
tags:
- ultralyticsplus
- yolov8
- ultralytics
- yolo
- vision
- object-detection
- pytorch
- awesome-yolov8-models
library_name: ultralytics
library_version: 8.0.21
inference: false
datasets:
- keremberke/table-extraction
model-index:
- name: keremberke/yolov8s-table-extraction
results:
- task:
type:... | 1,796 | [
[
-0.036712646484375,
-0.029266357421875,
0.042938232421875,
-0.025634765625,
-0.029449462890625,
-0.022216796875,
0.0105743408203125,
-0.03216552734375,
0.0211639404296875,
0.0230712890625,
-0.037384033203125,
-0.051513671875,
-0.02978515625,
-0.0025749206542... |
microsoft/deberta-base-mnli | 2021-12-09T13:36:31.000Z | [
"transformers",
"pytorch",
"rust",
"deberta",
"text-classification",
"deberta-v1",
"deberta-mnli",
"en",
"arxiv:2006.03654",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-classification | microsoft | null | null | microsoft/deberta-base-mnli | 3 | 23,030 | transformers | 2022-03-02T23:29:05 | ---
language: en
tags:
- deberta-v1
- deberta-mnli
tasks: mnli
thumbnail: https://huggingface.co/front/thumbnails/microsoft.png
license: mit
widget:
- text: "[CLS] I love you. [SEP] I like you. [SEP]"
---
## DeBERTa: Decoding-enhanced BERT with Disentangled Attention
[DeBERTa](https://arxiv.org/abs/2006.03654) impro... | 1,441 | [
[
-0.02337646484375,
-0.04473876953125,
0.0179901123046875,
0.0352783203125,
-0.019256591796875,
0.0147552490234375,
-0.00432586669921875,
-0.046356201171875,
0.01065826416015625,
0.0081024169921875,
-0.043853759765625,
-0.0299224853515625,
-0.072265625,
0.003... |
timm/vgg19_bn.tv_in1k | 2023-04-25T20:18:13.000Z | [
"timm",
"pytorch",
"safetensors",
"image-classification",
"dataset:imagenet-1k",
"arxiv:1409.1556",
"license:bsd-3-clause",
"region:us"
] | image-classification | timm | null | null | timm/vgg19_bn.tv_in1k | 0 | 23,029 | timm | 2023-04-25T20:16:20 | ---
tags:
- image-classification
- timm
library_name: timm
license: bsd-3-clause
datasets:
- imagenet-1k
---
# Model card for vgg19_bn.tv_in1k
A VGG image classification model. Trained on ImageNet-1k, original torchvision weights.
## Model Details
- **Model Type:** Image classification / feature backbone
- **Model St... | 3,646 | [
[
-0.03619384765625,
-0.03619384765625,
0.000782012939453125,
0.0031948089599609375,
-0.0306396484375,
-0.021575927734375,
-0.0202484130859375,
-0.0302886962890625,
0.01297760009765625,
0.0307159423828125,
-0.0298614501953125,
-0.0596923828125,
-0.055450439453125,... |
baichuan-inc/Baichuan2-7B-Chat | 2023-10-11T09:29:29.000Z | [
"transformers",
"pytorch",
"baichuan",
"text-generation",
"custom_code",
"en",
"zh",
"has_space",
"region:us"
] | text-generation | baichuan-inc | null | null | baichuan-inc/Baichuan2-7B-Chat | 96 | 23,018 | transformers | 2023-08-29T02:21:41 | ---
language:
- en
- zh
license_name: baichuan2-community-license
license_link: https://huggingface.co/baichuan-inc/Baichuan2-7B-Chat/blob/main/Community%20License%20for%20Baichuan2%20Model.pdf
tasks:
- text-generation
---
<!-- markdownlint-disable first-line-h1 -->
<!-- markdownlint-disable html -->
<div align=... | 13,351 | [
[
-0.0254974365234375,
-0.05267333984375,
0.0019092559814453125,
0.02880859375,
-0.0192413330078125,
-0.0032501220703125,
-0.02215576171875,
-0.030029296875,
0.02020263671875,
0.00798797607421875,
-0.034515380859375,
-0.03704833984375,
-0.047393798828125,
-0.0... |
castorini/monot5-3b-msmarco | 2021-04-03T13:48:44.000Z | [
"transformers",
"pytorch",
"t5",
"feature-extraction",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | feature-extraction | castorini | null | null | castorini/monot5-3b-msmarco | 0 | 22,988 | transformers | 2022-03-02T23:29:05 | This model is a T5-3B reranker fine-tuned on the MS MARCO passage dataset for 100k steps (or 10 epochs).
For more details on how to use it, check [pygaggle.ai](pygaggle.ai)
Paper describing the model: [Document Ranking with a Pretrained Sequence-to-Sequence Model](https://www.aclweb.org/anthology/2020.findings-emnlp.... | 324 | [
[
-0.007083892822265625,
-0.043609619140625,
0.0343017578125,
0.014678955078125,
-0.00867462158203125,
-0.0070037841796875,
0.0167388916015625,
-0.023223876953125,
0.0228271484375,
0.041961669921875,
-0.045684814453125,
-0.049407958984375,
-0.040313720703125,
... |
princeton-nlp/Sheared-LLaMA-1.3B | 2023-11-01T14:50:10.000Z | [
"transformers",
"pytorch",
"llama",
"text-generation",
"arxiv:2310.06694",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | princeton-nlp | null | null | princeton-nlp/Sheared-LLaMA-1.3B | 46 | 22,965 | transformers | 2023-10-10T15:22:13 | ---
license: apache-2.0
---
**Paper**: [https://arxiv.org/pdf/2310.06694.pdf](https://arxiv.org/pdf/2310.06694.pdf)
**Code**: https://github.com/princeton-nlp/LLM-Shearing
**Models**: [Sheared-LLaMA-1.3B](https://huggingface.co/princeton-nlp/Sheared-LLaMA-1.3B), [Sheared-LLaMA-2.7B](https://huggingface.co/princeto... | 2,729 | [
[
-0.0224151611328125,
-0.0543212890625,
0.011199951171875,
0.0428466796875,
-0.029052734375,
0.01206207275390625,
-0.00911712646484375,
-0.042877197265625,
0.0307159423828125,
0.0234222412109375,
-0.048126220703125,
-0.040283203125,
-0.058990478515625,
0.0086... |
bigcode/starcoder | 2023-10-05T09:24:35.000Z | [
"transformers",
"pytorch",
"gpt_bigcode",
"text-generation",
"code",
"dataset:bigcode/the-stack-dedup",
"arxiv:1911.02150",
"arxiv:2205.14135",
"arxiv:2207.14255",
"arxiv:2305.06161",
"license:bigcode-openrail-m",
"model-index",
"endpoints_compatible",
"has_space",
"text-generation-infer... | text-generation | bigcode | null | null | bigcode/starcoder | 2,433 | 22,939 | transformers | 2023-04-24T12:36:52 | ---
pipeline_tag: text-generation
inference: true
widget:
- text: 'def print_hello_world():'
example_title: Hello world
group: Python
license: bigcode-openrail-m
datasets:
- bigcode/the-stack-dedup
metrics:
- code_eval
library_name: transformers
tags:
- code
model-index:
- name: StarCoder
results:
- task:
... | 11,181 | [
[
-0.04345703125,
-0.03558349609375,
0.03076171875,
0.00951385498046875,
-0.0127410888671875,
-0.021087646484375,
-0.01390838623046875,
-0.0296630859375,
0.006805419921875,
0.02264404296875,
-0.042816162109375,
-0.033660888671875,
-0.056915283203125,
0.0032863... |
microsoft/DialoGPT-large | 2023-01-24T16:55:06.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"gpt2",
"text-generation",
"conversational",
"arxiv:1911.00536",
"license:mit",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | conversational | microsoft | null | null | microsoft/DialoGPT-large | 209 | 22,933 | transformers | 2022-03-02T23:29:05 | ---
thumbnail: https://huggingface.co/front/thumbnails/dialogpt.png
tags:
- conversational
license: mit
---
## A State-of-the-Art Large-scale Pretrained Response generation model (DialoGPT)
DialoGPT is a SOTA large-scale pretrained dialogue response generation model for multiturn conversations.
The [human evaluation... | 2,417 | [
[
-0.02996826171875,
-0.0712890625,
0.0033855438232421875,
0.008941650390625,
-0.0125732421875,
0.0119781494140625,
-0.0015096664428710938,
-0.01471710205078125,
0.01495361328125,
0.03350830078125,
-0.0628662109375,
-0.0098876953125,
-0.032623291015625,
-0.003... |
ahotrod/electra_large_discriminator_squad2_512 | 2020-12-11T21:31:42.000Z | [
"transformers",
"pytorch",
"tf",
"electra",
"question-answering",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | question-answering | ahotrod | null | null | ahotrod/electra_large_discriminator_squad2_512 | 5 | 22,893 | transformers | 2022-03-02T23:29:05 | ## ELECTRA_large_discriminator language model fine-tuned on SQuAD2.0
### with the following results:
```
"exact": 87.09677419354838,
"f1": 89.98343832723452,
"total": 11873,
"HasAns_exact": 84.66599190283401,
"HasAns_f1": 90.44759839056285,
"HasAns_total": 5928,
"NoAns_exact": 89.52060555088309,
"NoAn... | 1,472 | [
[
-0.0270843505859375,
-0.055938720703125,
0.0192108154296875,
0.007419586181640625,
-0.01122283935546875,
0.0215911865234375,
-0.0251007080078125,
-0.028900146484375,
0.004726409912109375,
0.0294036865234375,
-0.04400634765625,
-0.0474853515625,
-0.04562377929687... |
dreamlike-art/dreamlike-anime-1.0 | 2023-03-13T01:04:40.000Z | [
"diffusers",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"image-to-image",
"anime",
"en",
"license:other",
"has_space",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | dreamlike-art | null | null | dreamlike-art/dreamlike-anime-1.0 | 214 | 22,887 | diffusers | 2023-01-08T03:47:50 | ---
language:
- en
license: other
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- image-to-image
- diffusers
- anime
inference: false
---
# Dreamlike Anime 1.0 is a high quality anime model, made by [dreamlike.art](https://dreamlike.art/).
# If you want to use dreamlike models on your website/... | 5,063 | [
[
-0.039093017578125,
-0.05682373046875,
0.02386474609375,
0.035400390625,
-0.032501220703125,
-0.017364501953125,
0.01337432861328125,
-0.04388427734375,
0.06024169921875,
0.0430908203125,
-0.05841064453125,
-0.0455322265625,
-0.03704833984375,
-0.00547790527... |
Helsinki-NLP/opus-mt-ja-en | 2023-08-16T11:59:08.000Z | [
"transformers",
"pytorch",
"tf",
"marian",
"text2text-generation",
"translation",
"ja",
"en",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | translation | Helsinki-NLP | null | null | Helsinki-NLP/opus-mt-ja-en | 29 | 22,799 | transformers | 2022-03-02T23:29:04 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-ja-en
* source languages: ja
* target languages: en
* OPUS readme: [ja-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/ja-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... | 818 | [
[
-0.019927978515625,
-0.0343017578125,
0.01873779296875,
0.027252197265625,
-0.031494140625,
-0.0279083251953125,
-0.034332275390625,
-0.006824493408203125,
0.006092071533203125,
0.037200927734375,
-0.051025390625,
-0.039703369140625,
-0.045074462890625,
0.01... |
naver-clova-ix/donut-base | 2022-08-13T08:27:12.000Z | [
"transformers",
"pytorch",
"vision-encoder-decoder",
"donut",
"image-to-text",
"vision",
"arxiv:2111.15664",
"license:mit",
"endpoints_compatible",
"has_space",
"region:us"
] | image-to-text | naver-clova-ix | null | null | naver-clova-ix/donut-base | 94 | 22,636 | transformers | 2022-07-19T13:49:17 | ---
license: mit
tags:
- donut
- image-to-text
- vision
---
# Donut (base-sized model, pre-trained only)
Donut model pre-trained-only. It was introduced in the paper [OCR-free Document Understanding Transformer](https://arxiv.org/abs/2111.15664) by Geewok et al. and first released in [this repository](https://github... | 2,197 | [
[
-0.0239410400390625,
-0.041229248046875,
0.0247955322265625,
-0.0170135498046875,
-0.0028095245361328125,
-0.00975799560546875,
-0.007354736328125,
-0.029998779296875,
0.02099609375,
0.047576904296875,
-0.042633056640625,
-0.0159759521484375,
-0.056304931640625,... |
TheBloke/Yarn-Llama-2-13B-128K-GPTQ | 2023-09-27T12:47:00.000Z | [
"transformers",
"safetensors",
"llama",
"text-generation",
"custom_code",
"dataset:pg19",
"arxiv:2309.00071",
"license:llama2",
"text-generation-inference",
"region:us"
] | text-generation | TheBloke | null | null | TheBloke/Yarn-Llama-2-13B-128K-GPTQ | 16 | 22,557 | transformers | 2023-09-01T11:17:06 | ---
license: llama2
library_name: transformers
datasets:
- pg19
metrics:
- perplexity
model_name: Yarn Llama 2 13B 128K
base_model: NousResearch/Yarn-Llama-2-13b-128k
inference: false
model_creator: NousResearch
model_type: llama
prompt_template: '{prompt}
'
quantized_by: TheBloke
---
<!-- header start -->
<!-- 200... | 16,559 | [
[
-0.035491943359375,
-0.058441162109375,
0.01446533203125,
0.01535797119140625,
-0.031280517578125,
-0.0014972686767578125,
0.005504608154296875,
-0.04296875,
0.02996826171875,
0.027099609375,
-0.0496826171875,
-0.04010009765625,
-0.033905029296875,
0.0081634... |
KoboldAI/fairseq-dense-125M | 2022-09-11T22:03:43.000Z | [
"transformers",
"pytorch",
"xglm",
"text-generation",
"en",
"arxiv:2112.10684",
"endpoints_compatible",
"has_space",
"region:us"
] | text-generation | KoboldAI | null | null | KoboldAI/fairseq-dense-125M | 3 | 22,508 | transformers | 2022-03-02T23:29:04 | ---
language: en
---
This is a Hugging Face transformers-compatible conversion of the original dense 125M-parameter model from the paper "[Efficient Large Scale Language Modeling with Mixtures of Experts](https://arxiv.org/abs/2112.10684)" from Artetxe et al. Please refer to the original model card, which can be found ... | 408 | [
[
-0.054443359375,
-0.060028076171875,
0.017974853515625,
0.0266571044921875,
-0.0163726806640625,
-0.04437255859375,
-0.02349853515625,
-0.0195159912109375,
0.038482666015625,
0.064208984375,
-0.05853271484375,
-0.01212310791015625,
-0.03680419921875,
-0.0180... |
microsoft/layoutlmv3-large | 2022-09-16T03:26:15.000Z | [
"transformers",
"pytorch",
"tf",
"layoutlmv3",
"en",
"arxiv:2204.08387",
"license:cc-by-nc-sa-4.0",
"endpoints_compatible",
"region:us"
] | null | microsoft | null | null | microsoft/layoutlmv3-large | 51 | 22,461 | transformers | 2022-04-18T06:56:58 | ---
language: en
license: cc-by-nc-sa-4.0
---
# LayoutLMv3
[Microsoft Document AI](https://www.microsoft.com/en-us/research/project/document-ai/) | [GitHub](https://aka.ms/layoutlmv3)
## Model description
LayoutLMv3 is a pre-trained multimodal Transformer for Document AI with unified text and image masking. The sim... | 1,664 | [
[
-0.0272064208984375,
-0.0267486572265625,
0.031707763671875,
0.0300140380859375,
-0.0165252685546875,
-0.00972747802734375,
0.0167694091796875,
-0.01076507568359375,
-0.0102081298828125,
0.038818359375,
-0.040771484375,
-0.03900146484375,
-0.036529541015625,
... |
EleutherAI/pythia-160m-deduped | 2023-07-09T16:04:57.000Z | [
"transformers",
"pytorch",
"safetensors",
"gpt_neox",
"text-generation",
"causal-lm",
"pythia",
"en",
"dataset:EleutherAI/the_pile_deduplicated",
"arxiv:2304.01373",
"arxiv:2101.00027",
"arxiv:2201.07311",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"text-generation-infe... | text-generation | EleutherAI | null | null | EleutherAI/pythia-160m-deduped | 1 | 22,458 | transformers | 2023-02-08T21:50:19 | ---
language:
- en
tags:
- pytorch
- causal-lm
- pythia
license: apache-2.0
datasets:
- EleutherAI/the_pile_deduplicated
---
The *Pythia Scaling Suite* is a collection of models developed to facilitate
interpretability research [(see paper)](https://arxiv.org/pdf/2304.01373.pdf).
It contains two sets of eight models... | 13,662 | [
[
-0.0251922607421875,
-0.059661865234375,
0.0252838134765625,
0.0037822723388671875,
-0.0171966552734375,
-0.01468658447265625,
-0.0175933837890625,
-0.032135009765625,
0.014495849609375,
0.013275146484375,
-0.026214599609375,
-0.0214691162109375,
-0.032958984375... |
facebook/dinov2-giant | 2023-09-06T11:23:25.000Z | [
"transformers",
"pytorch",
"safetensors",
"dinov2",
"feature-extraction",
"dino",
"vision",
"arxiv:2304.07193",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | feature-extraction | facebook | null | null | facebook/dinov2-giant | 10 | 22,394 | transformers | 2023-07-17T16:49:29 | ---
license: apache-2.0
tags:
- dino
- vision
---
# Vision Transformer (giant-sized model) trained using DINOv2
Vision Transformer (ViT) model trained using the DINOv2 method. It was introduced in the paper [DINOv2: Learning Robust Visual Features without Supervision](https://arxiv.org/abs/2304.07193) by Oquab et al.... | 3,030 | [
[
-0.03790283203125,
-0.0313720703125,
0.007526397705078125,
-0.009246826171875,
-0.036163330078125,
-0.0032444000244140625,
0.006282806396484375,
-0.032470703125,
0.0227508544921875,
0.0379638671875,
-0.03289794921875,
-0.015655517578125,
-0.052581787109375,
... |
bigscience/bloom-1b1 | 2023-09-26T09:16:38.000Z | [
"transformers",
"pytorch",
"jax",
"onnx",
"safetensors",
"bloom",
"text-generation",
"ak",
"ar",
"as",
"bm",
"bn",
"ca",
"code",
"en",
"es",
"eu",
"fon",
"fr",
"gu",
"hi",
"id",
"ig",
"ki",
"kn",
"lg",
"ln",
"ml",
"mr",
"ne",
"nso",
"ny",
"or",
"pa",... | text-generation | bigscience | null | null | bigscience/bloom-1b1 | 42 | 22,387 | transformers | 2022-05-19T11:51:48 | ---
license: bigscience-bloom-rail-1.0
language:
- ak
- ar
- as
- bm
- bn
- ca
- code
- en
- es
- eu
- fon
- fr
- gu
- hi
- id
- ig
- ki
- kn
- lg
- ln
- ml
- mr
- ne
- nso
- ny
- or
- pa
- pt
- rn
- rw
- sn
- st
- sw
- ta
- te
- tn
- ts
- tum
- tw
- ur
- vi
- wo
- xh
- yo
- zh
- zhs
- zht
- zu
pipeline_tag: text-gener... | 20,632 | [
[
-0.0285186767578125,
-0.0545654296875,
0.033355712890625,
0.00844573974609375,
-0.00640106201171875,
-0.015045166015625,
-0.036651611328125,
-0.0421142578125,
0.00650787353515625,
0.01727294921875,
-0.0278472900390625,
-0.03759765625,
-0.05145263671875,
0.00... |
Salesforce/blip-itm-base-coco | 2023-08-01T14:49:10.000Z | [
"transformers",
"pytorch",
"tf",
"blip",
"image-text-matching",
"arxiv:2201.12086",
"license:bsd-3-clause",
"endpoints_compatible",
"has_space",
"region:us"
] | null | Salesforce | null | null | Salesforce/blip-itm-base-coco | 3 | 22,336 | transformers | 2022-12-12T17:53:18 | ---
pipeline_tags: 'other'
tags:
- image-text-matching
languages:
- en
license: bsd-3-clause
---
# BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation
Model card for BLIP trained on image-text matching - base architecture (with ViT base backbone) trained on COC... | 4,815 | [
[
-0.0220489501953125,
-0.044403076171875,
-0.0031337738037109375,
0.045745849609375,
-0.0290069580078125,
0.0010747909545898438,
-0.0361328125,
-0.05035400390625,
-0.0009140968322753906,
0.021820068359375,
-0.0256500244140625,
-0.038818359375,
-0.03271484375,
... |
wavymulder/Analog-Diffusion | 2023-01-27T22:30:51.000Z | [
"diffusers",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"safetensors",
"en",
"license:creativeml-openrail-m",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | wavymulder | null | null | wavymulder/Analog-Diffusion | 849 | 22,324 | diffusers | 2022-12-10T20:14:02 | ---
language:
- en
thumbnail: "https://huggingface.co/wavymulder/Analog-Diffusion/resolve/main/images/page1.jpg"
license: creativeml-openrail-m
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- safetensors
- diffusers
inference: true
---
**Analog Diffusion**
![Header](https://huggingface.co/wav... | 1,622 | [
[
-0.06689453125,
-0.08087158203125,
0.059173583984375,
-0.006931304931640625,
-0.047576904296875,
-0.0087432861328125,
0.021392822265625,
-0.0283660888671875,
0.05584716796875,
0.041290283203125,
-0.044219970703125,
-0.042938232421875,
-0.04241943359375,
-0.0... |
sentence-transformers/stsb-roberta-large | 2022-06-15T20:28:37.000Z | [
"sentence-transformers",
"pytorch",
"tf",
"jax",
"roberta",
"feature-extraction",
"sentence-similarity",
"transformers",
"arxiv:1908.10084",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | sentence-similarity | sentence-transformers | null | null | sentence-transformers/stsb-roberta-large | 3 | 22,219 | sentence-transformers | 2022-03-02T23:29:05 | ---
pipeline_tag: sentence-similarity
license: apache-2.0
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
**⚠️ This model is deprecated. Please don't use it as it produces sentence embeddings of low quality. You can find recommended sentence embedding models here: [SBERT.net... | 3,918 | [
[
-0.0160369873046875,
-0.06292724609375,
0.0262908935546875,
0.0309906005859375,
-0.027923583984375,
-0.031158447265625,
-0.0298309326171875,
-0.0074310302734375,
0.01383209228515625,
0.0322265625,
-0.038116455078125,
-0.03460693359375,
-0.057525634765625,
0.... |
flaubert/flaubert_base_cased | 2021-05-19T16:54:23.000Z | [
"transformers",
"pytorch",
"flaubert",
"fill-mask",
"bert",
"language-model",
"flue",
"french",
"bert-base",
"flaubert-base",
"cased",
"fr",
"dataset:flaubert",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | flaubert | null | null | flaubert/flaubert_base_cased | 3 | 22,209 | transformers | 2022-03-02T23:29:05 | ---
language: fr
license: mit
datasets:
- flaubert
metrics:
- flue
tags:
- bert
- language-model
- flaubert
- flue
- french
- bert-base
- flaubert-base
- cased
---
# FlauBERT: Unsupervised Language Model Pre-training for French
**FlauBERT** is a French BERT trained on a very large and heterogeneous French corpus. M... | 4,483 | [
[
-0.02520751953125,
-0.055450439453125,
0.026275634765625,
0.01352691650390625,
-0.000988006591796875,
0.00377655029296875,
-0.0203704833984375,
-0.0079193115234375,
0.0252227783203125,
0.03680419921875,
-0.030914306640625,
-0.035552978515625,
-0.04705810546875,
... |
facebook/mbart-large-50-one-to-many-mmt | 2023-03-28T10:00:25.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"mbart",
"text2text-generation",
"mbart-50",
"multilingual",
"ar",
"cs",
"de",
"en",
"es",
"et",
"fi",
"fr",
"gu",
"hi",
"it",
"ja",
"kk",
"ko",
"lt",
"lv",
"my",
"ne",
"nl",
"ro",
"ru",
"si",
"tr",
"vi",
"zh",
... | text2text-generation | facebook | null | null | facebook/mbart-large-50-one-to-many-mmt | 26 | 22,158 | transformers | 2022-03-02T23:29:05 | ---
language:
- multilingual
- ar
- cs
- de
- en
- es
- et
- fi
- fr
- gu
- hi
- it
- ja
- kk
- ko
- lt
- lv
- my
- ne
- nl
- ro
- ru
- si
- tr
- vi
- zh
- af
- az
- bn
- fa
- he
- hr
- id
- ka
- km
- mk
- ml
- mn
- mr
- pl
- ps
- pt
- sv
- sw
- ta
- te
- th
- tl
- uk
- ur
- xh
- gl
- sl
tags:
- mbart-50
---
# mBART... | 3,420 | [
[
-0.03839111328125,
-0.0302581787109375,
0.004314422607421875,
0.035308837890625,
-0.02728271484375,
0.00801849365234375,
-0.027435302734375,
-0.02679443359375,
0.0211181640625,
0.01377105712890625,
-0.045318603515625,
-0.044708251953125,
-0.049530029296875,
... |
hfl/chinese-roberta-wwm-ext | 2022-03-01T09:13:56.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"zh",
"arxiv:1906.08101",
"arxiv:2004.13922",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | hfl | null | null | hfl/chinese-roberta-wwm-ext | 191 | 22,145 | transformers | 2022-03-02T23:29:05 | ---
language:
- zh
tags:
- bert
license: "apache-2.0"
---
# Please use 'Bert' related functions to load this model!
## Chinese BERT with Whole Word Masking
For further accelerating Chinese natural language processing, we provide **Chinese pre-trained BERT with Whole Word Masking**.
**[Pre-Training with Whole Word ... | 2,066 | [
[
-0.027862548828125,
-0.05731201171875,
0.022430419921875,
0.0367431640625,
-0.0292205810546875,
-0.014495849609375,
-0.041351318359375,
-0.052154541015625,
0.023773193359375,
0.033721923828125,
-0.035491943359375,
-0.03887939453125,
-0.0394287109375,
0.00013... |
WizardLM/WizardLM-70B-V1.0 | 2023-09-09T06:46:08.000Z | [
"transformers",
"pytorch",
"llama",
"text-generation",
"arxiv:2304.12244",
"arxiv:2306.08568",
"arxiv:2308.09583",
"license:llama2",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | WizardLM | null | null | WizardLM/WizardLM-70B-V1.0 | 132 | 22,125 | transformers | 2023-08-09T05:26:23 | ---
license: llama2
---
## WizardLM: Empowering Large Pre-Trained Language Models to Follow Complex Instructions
<p align="center">
🤗 <a href="https://huggingface.co/WizardLM" target="_blank">HF Repo</a> •🐱 <a href="https://github.com/nlpxucan/WizardLM" target="_blank">Github Repo</a> • 🐦 <a href="https://twi... | 9,768 | [
[
-0.048736572265625,
-0.037750244140625,
-0.0017328262329101562,
0.0249786376953125,
0.00736236572265625,
-0.006443023681640625,
-0.0006923675537109375,
-0.0307769775390625,
0.0151519775390625,
0.026611328125,
-0.050201416015625,
-0.048248291015625,
-0.0408020019... |
facebook/mask2former-swin-large-cityscapes-semantic | 2023-09-07T15:38:57.000Z | [
"transformers",
"pytorch",
"safetensors",
"mask2former",
"vision",
"image-segmentation",
"dataset:coco",
"arxiv:2112.01527",
"arxiv:2107.06278",
"license:other",
"endpoints_compatible",
"has_space",
"region:us"
] | image-segmentation | facebook | null | null | facebook/mask2former-swin-large-cityscapes-semantic | 6 | 22,114 | transformers | 2023-01-05T00:18:47 | ---
license: other
tags:
- vision
- image-segmentation
datasets:
- coco
widget:
- src: http://images.cocodataset.org/val2017/000000039769.jpg
example_title: Cats
- src: http://images.cocodataset.org/val2017/000000039770.jpg
example_title: Castle
---
# Mask2Former
Mask2Former model trained on Cityscapes semantic s... | 3,185 | [
[
-0.04046630859375,
-0.04644775390625,
0.03240966796875,
0.0206298828125,
-0.0154571533203125,
-0.0159149169921875,
0.00846099853515625,
-0.058380126953125,
0.01091766357421875,
0.05023193359375,
-0.053314208984375,
-0.03594970703125,
-0.05615234375,
-0.02073... |
superb/hubert-large-superb-er | 2021-11-04T16:03:28.000Z | [
"transformers",
"pytorch",
"hubert",
"audio-classification",
"speech",
"audio",
"en",
"dataset:superb",
"arxiv:2105.01051",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | audio-classification | superb | null | null | superb/hubert-large-superb-er | 13 | 22,071 | transformers | 2022-03-02T23:29:05 | ---
language: en
datasets:
- superb
tags:
- speech
- audio
- hubert
- audio-classification
widget:
- example_title: IEMOCAP clip "happy"
src: https://cdn-media.huggingface.co/speech_samples/IEMOCAP_Ses01F_impro03_F013.wav
- example_title: IEMOCAP clip "neutral"
src: https://cdn-media.huggingface.co/speech_samples/I... | 3,494 | [
[
-0.035186767578125,
-0.0305023193359375,
0.0218963623046875,
0.0201416015625,
-0.005107879638671875,
-0.004718780517578125,
-0.0238189697265625,
-0.03802490234375,
0.00832366943359375,
0.018463134765625,
-0.043212890625,
-0.042327880859375,
-0.042266845703125,
... |
openlm-research/open_llama_7b_v2 | 2023-07-07T21:26:13.000Z | [
"transformers",
"pytorch",
"llama",
"text-generation",
"dataset:tiiuae/falcon-refinedweb",
"dataset:bigcode/starcoderdata",
"dataset:togethercomputer/RedPajama-Data-1T",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | openlm-research | null | null | openlm-research/open_llama_7b_v2 | 91 | 21,971 | transformers | 2023-07-06T08:23:04 | ---
license: apache-2.0
datasets:
- tiiuae/falcon-refinedweb
- bigcode/starcoderdata
- togethercomputer/RedPajama-Data-1T
library_name: transformers
---
# OpenLLaMA: An Open Reproduction of LLaMA
**TL;DR**: we are releasing our public preview of OpenLLaMA, a permissively licensed open source reproduction of Meta AI’s... | 11,764 | [
[
-0.025360107421875,
-0.0531005859375,
0.01885986328125,
0.033050537109375,
-0.0172119140625,
-0.004253387451171875,
-0.0240478515625,
-0.0479736328125,
0.02447509765625,
0.0208740234375,
-0.03375244140625,
-0.045867919921875,
-0.04754638671875,
0.00608444213... |
tomaarsen/span-marker-bert-base-acronyms | 2023-09-27T12:51:40.000Z | [
"span-marker",
"pytorch",
"tensorboard",
"safetensors",
"token-classification",
"ner",
"named-entity-recognition",
"generated_from_span_marker_trainer",
"en",
"dataset:acronym_identification",
"license:apache-2.0",
"model-index",
"co2_eq_emissions",
"region:us",
"has_space"
] | token-classification | tomaarsen | null | null | tomaarsen/span-marker-bert-base-acronyms | 5 | 21,969 | span-marker | 2023-08-13T22:25:04 | ---
language:
- en
license: apache-2.0
library_name: span-marker
tags:
- span-marker
- token-classification
- ner
- named-entity-recognition
- generated_from_span_marker_trainer
datasets:
- acronym_identification
metrics:
- precision
- recall
- f1
widget:
- text: "Here, DA = direct assessment, RR = relative ranking, DS... | 8,012 | [
[
-0.041229248046875,
-0.048828125,
0.01551055908203125,
0.016876220703125,
-0.0147857666015625,
0.0021724700927734375,
-0.0156097412109375,
-0.040435791015625,
0.03289794921875,
0.01041412353515625,
-0.047607421875,
-0.046142578125,
-0.05133056640625,
0.00240... |
PY007/TinyLlama-1.1B-intermediate-step-480k-1T | 2023-10-02T05:15:59.000Z | [
"transformers",
"pytorch",
"llama",
"text-generation",
"en",
"dataset:cerebras/SlimPajama-627B",
"dataset:bigcode/starcoderdata",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | PY007 | null | null | PY007/TinyLlama-1.1B-intermediate-step-480k-1T | 23 | 21,879 | transformers | 2023-10-02T04:01:40 | ---
license: apache-2.0
datasets:
- cerebras/SlimPajama-627B
- bigcode/starcoderdata
language:
- en
---
<div align="center">
# TinyLlama-1.1B
</div>
https://github.com/jzhang38/TinyLlama
The TinyLlama project aims to **pretrain** a **1.1B Llama model on 3 trillion tokens**. With some proper optimization, we can achi... | 1,893 | [
[
-0.02154541015625,
-0.04608154296875,
0.038360595703125,
0.0184326171875,
-0.046630859375,
-0.00325775146484375,
-0.0138702392578125,
-0.02593994140625,
0.0223388671875,
0.0126800537109375,
-0.055023193359375,
-0.023956298828125,
-0.037322998046875,
-0.00975... |
distil-whisper/distil-medium.en | 2023-11-06T10:53:42.000Z | [
"transformers",
"pytorch",
"jax",
"tensorboard",
"onnx",
"safetensors",
"whisper",
"automatic-speech-recognition",
"audio",
"transformers.js",
"en",
"arxiv:2311.00430",
"arxiv:2210.13352",
"license:mit",
"endpoints_compatible",
"has_space",
"region:us"
] | automatic-speech-recognition | distil-whisper | null | null | distil-whisper/distil-medium.en | 43 | 21,860 | transformers | 2023-10-24T15:49:07 | ---
language:
- en
tags:
- audio
- automatic-speech-recognition
- transformers.js
widget:
- example_title: LibriSpeech sample 1
src: https://cdn-media.huggingface.co/speech_samples/sample1.flac
- example_title: LibriSpeech sample 2
src: https://cdn-media.huggingface.co/speech_samples/sample2.flac
pipeline_tag: auto... | 20,236 | [
[
-0.022857666015625,
-0.05487060546875,
0.0186309814453125,
0.0295257568359375,
-0.0200958251953125,
0.00521087646484375,
-0.018341064453125,
-0.03082275390625,
0.0025730133056640625,
0.006927490234375,
-0.04052734375,
-0.033843994140625,
-0.06451416015625,
-... |
SG161222/RealVisXL_V2.0 | 2023-09-26T10:28:59.000Z | [
"diffusers",
"license:openrail++",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionXLPipeline",
"region:us"
] | null | SG161222 | null | null | SG161222/RealVisXL_V2.0 | 22 | 21,704 | diffusers | 2023-09-26T05:43:16 | ---
license: openrail++
---
<b>It's important! Read it!</b><br>
The model is still in the training phase. This is not the final version and may contain artifacts and perform poorly in some cases.<br>
The model is aimed at photorealism. Can produce sfw and nsfw images of decent quality.<br>
CivitAI Page: https://civita... | 642 | [
[
-0.045654296875,
-0.04437255859375,
0.037261962890625,
0.034210205078125,
-0.052276611328125,
0.007091522216796875,
0.034271240234375,
-0.05584716796875,
0.0130615234375,
0.03887939453125,
-0.0810546875,
-0.0254364013671875,
-0.0196533203125,
-0.005237579345... |
knkarthick/MEETING_SUMMARY | 2023-03-27T15:08:14.000Z | [
"transformers",
"pytorch",
"tf",
"safetensors",
"bart",
"text2text-generation",
"seq2seq",
"summarization",
"en",
"dataset:cnndaily/newyorkdaily/xsum/samsum/dialogsum/AMI",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | summarization | knkarthick | null | null | knkarthick/MEETING_SUMMARY | 158 | 21,637 | transformers | 2022-03-02T23:29:05 | ---
language: en
license: apache-2.0
tags:
- bart
- seq2seq
- summarization
datasets:
- cnndaily/newyorkdaily/xsum/samsum/dialogsum/AMI
metrics:
- rouge
widget:
- text: 'Hi, I''m David and I''m supposed to be an industrial designer. Um, I just
got the project announcement about what the project is. Designing a remo... | 62,352 | [
[
-0.0665283203125,
-0.0418701171875,
0.0291900634765625,
0.01328277587890625,
-0.0286865234375,
-0.003307342529296875,
-0.0014066696166992188,
-0.04486083984375,
0.048095703125,
0.0173797607421875,
-0.0234527587890625,
-0.01171875,
-0.02508544921875,
-0.00313... |
stanfordnlp/stanza-en | 2023-10-31T15:24:28.000Z | [
"stanza",
"token-classification",
"en",
"license:apache-2.0",
"region:us"
] | token-classification | stanfordnlp | null | null | stanfordnlp/stanza-en | 9 | 21,627 | stanza | 2022-03-02T23:29:05 | ---
tags:
- stanza
- token-classification
library_name: stanza
language: en
license: apache-2.0
---
# Stanza model for English (en)
Stanza is a collection of accurate and efficient tools for the linguistic analysis of many human languages. Starting from raw text to syntactic analysis and entity recognition, Stanza brin... | 680 | [
[
-0.027557373046875,
-0.053985595703125,
0.01654052734375,
0.0367431640625,
-0.0203399658203125,
-0.01197052001953125,
-0.0151824951171875,
-0.045379638671875,
0.020172119140625,
0.031707763671875,
-0.04302978515625,
-0.03485107421875,
-0.0269927978515625,
0.... |
mrm8488/longformer-base-4096-finetuned-squadv2 | 2022-12-05T13:36:25.000Z | [
"transformers",
"pytorch",
"tf",
"longformer",
"question-answering",
"QA",
"long context",
"Q&A",
"en",
"dataset:squad_v2",
"arxiv:2004.05150",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | question-answering | mrm8488 | null | null | mrm8488/longformer-base-4096-finetuned-squadv2 | 10 | 21,614 | transformers | 2022-03-02T23:29:05 | ---
language: en
tags:
- QA
- long context
- Q&A
datasets:
- squad_v2
model-index:
- name: mrm8488/longformer-base-4096-finetuned-squadv2
results:
- task:
type: question-answering
name: Question Answering
dataset:
name: squad_v2
type: squad_v2
config: squad_v2
split: validati... | 4,410 | [
[
-0.034393310546875,
-0.04937744140625,
0.006847381591796875,
0.04217529296875,
-0.003261566162109375,
0.0008668899536132812,
-0.0228729248046875,
-0.033447265625,
0.03216552734375,
0.0273284912109375,
-0.0731201171875,
-0.0265045166015625,
-0.0458984375,
0.0... |
Helsinki-NLP/opus-mt-en-nl | 2023-08-16T11:30:40.000Z | [
"transformers",
"pytorch",
"tf",
"rust",
"marian",
"text2text-generation",
"translation",
"en",
"nl",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | translation | Helsinki-NLP | null | null | Helsinki-NLP/opus-mt-en-nl | 2 | 21,612 | transformers | 2022-03-02T23:29:04 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-en-nl
* source languages: en
* target languages: nl
* OPUS readme: [en-nl](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/en-nl/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... | 818 | [
[
-0.017669677734375,
-0.034088134765625,
0.018463134765625,
0.032806396484375,
-0.03472900390625,
-0.0295867919921875,
-0.033721923828125,
-0.0087432861328125,
0.0032253265380859375,
0.035552978515625,
-0.05126953125,
-0.041412353515625,
-0.042449951171875,
0... |
facebook/mask2former-swin-base-coco-panoptic | 2023-09-06T19:14:44.000Z | [
"transformers",
"pytorch",
"safetensors",
"mask2former",
"vision",
"image-segmentation",
"dataset:coco",
"arxiv:2112.01527",
"arxiv:2107.06278",
"license:other",
"endpoints_compatible",
"has_space",
"region:us"
] | image-segmentation | facebook | null | null | facebook/mask2former-swin-base-coco-panoptic | 9 | 21,589 | transformers | 2023-01-02T16:06:26 | ---
license: other
tags:
- vision
- image-segmentation
datasets:
- coco
widget:
- src: http://images.cocodataset.org/val2017/000000039769.jpg
example_title: Cats
- src: http://images.cocodataset.org/val2017/000000039770.jpg
example_title: Castle
---
# Mask2Former
Mask2Former model trained on COCO panoptic segment... | 3,190 | [
[
-0.047760009765625,
-0.046142578125,
0.012451171875,
0.03363037109375,
-0.0228271484375,
-0.00983428955078125,
0.0090789794921875,
-0.059112548828125,
0.0187530517578125,
0.04925537109375,
-0.04925537109375,
-0.0195465087890625,
-0.06280517578125,
-0.0248260... |
anas-awadalla/mpt-1b-redpajama-200b | 2023-08-05T06:19:59.000Z | [
"transformers",
"pytorch",
"mosaic_gpt",
"text-generation",
"custom_code",
"dataset:togethercomputer/RedPajama-Data-1T",
"arxiv:2302.13971",
"arxiv:2205.14135",
"arxiv:2108.12409",
"license:apache-2.0",
"has_space",
"region:us"
] | text-generation | anas-awadalla | null | null | anas-awadalla/mpt-1b-redpajama-200b | 2 | 21,585 | transformers | 2023-05-25T00:58:32 | ---
license: apache-2.0
datasets:
- togethercomputer/RedPajama-Data-1T
---
# MPT-1b-RedPajama-200b
MPT-1b-RedPajama-200b is a 1.3 billion parameter decoder-only transformer trained on the [RedPajama dataset](https://huggingface.co/datasets/togethercomputer/RedPajama-Data-1T).
The model was trained for 200B tokens by ... | 3,710 | [
[
-0.038482666015625,
-0.0206298828125,
0.0192718505859375,
0.036163330078125,
-0.0340576171875,
-0.0024509429931640625,
-0.000621795654296875,
-0.03302001953125,
0.021728515625,
0.03887939453125,
-0.049896240234375,
-0.04107666015625,
-0.056060791015625,
0.01... |
microsoft/xclip-base-patch16-zero-shot | 2023-09-12T12:13:40.000Z | [
"transformers",
"pytorch",
"safetensors",
"xclip",
"feature-extraction",
"vision",
"video-classification",
"en",
"arxiv:2208.02816",
"license:mit",
"model-index",
"endpoints_compatible",
"has_space",
"region:us"
] | feature-extraction | microsoft | null | null | microsoft/xclip-base-patch16-zero-shot | 16 | 21,570 | transformers | 2022-09-07T17:52:51 | ---
language: en
license: mit
tags:
- vision
- video-classification
model-index:
- name: nielsr/xclip-base-patch16-zero-shot
results:
- task:
type: video-classification
dataset:
name: HMDB-51
type: hmdb-51
metrics:
- type: top-1 accuracy
value: 44.6
- task:
type: video-cl... | 3,017 | [
[
-0.04644775390625,
-0.0352783203125,
0.0252532958984375,
0.0012578964233398438,
-0.02496337890625,
0.003520965576171875,
-0.0157928466796875,
-0.01537322998046875,
0.02581787109375,
0.0229034423828125,
-0.06689453125,
-0.0462646484375,
-0.05963134765625,
-0.... |
facebook/rag-token-nq | 2021-03-12T10:55:22.000Z | [
"transformers",
"pytorch",
"tf",
"rag",
"en",
"dataset:wiki_dpr",
"arxiv:2005.11401",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | null | facebook | null | null | facebook/rag-token-nq | 48 | 21,545 | transformers | 2022-03-02T23:29:05 | ---
language: en
license: apache-2.0
datasets:
- wiki_dpr
thumbnail: https://huggingface.co/front/thumbnails/facebook.png
---
## RAG
This is the RAG-Token Model of the the paper [Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks](https://arxiv.org/pdf/2005.11401.pdf)
by Patrick Lewis, Ethan Perez, Alek... | 1,723 | [
[
-0.0255584716796875,
-0.04718017578125,
0.0152130126953125,
0.0008134841918945312,
-0.0189361572265625,
0.007595062255859375,
-0.0069732666015625,
-0.00705718994140625,
0.022613525390625,
0.03314208984375,
-0.03192138671875,
-0.0027790069580078125,
-0.0441589355... |
ElKulako/cryptobert | 2022-09-01T21:54:02.000Z | [
"transformers",
"pytorch",
"roberta",
"text-classification",
"cryptocurrency",
"crypto",
"BERT",
"sentiment classification",
"NLP",
"bitcoin",
"ethereum",
"shib",
"social media",
"sentiment analysis",
"cryptocurrency sentiment analysis",
"en",
"dataset:ElKulako/stocktwits-crypto",
... | text-classification | ElKulako | null | null | ElKulako/cryptobert | 50 | 21,418 | transformers | 2022-06-20T02:29:26 | ---
datasets:
- ElKulako/stocktwits-crypto
language:
- en
tags:
- cryptocurrency
- crypto
- BERT
- sentiment classification
- NLP
- bitcoin
- ethereum
- shib
- social media
- sentiment analysis
- cryptocurrency sentiment analysis
---
# CryptoBERT
CryptoBERT is a pre-trained NLP model to analyse the language and sent... | 3,573 | [
[
-0.04290771484375,
-0.060394287109375,
0.00559234619140625,
0.0259246826171875,
-0.04656982421875,
0.0185089111328125,
-0.0038471221923828125,
-0.04144287109375,
0.044036865234375,
0.0245361328125,
-0.0221405029296875,
-0.0650634765625,
-0.0631103515625,
0.0... |
soleimanian/financial-roberta-large-sentiment | 2022-10-12T21:04:39.000Z | [
"transformers",
"pytorch",
"roberta",
"text-classification",
"Sentiment",
"RoBERTa",
"Financial Statements",
"Accounting",
"Finance",
"Business",
"ESG",
"CSR Reports",
"Financial News",
"Earnings Call Transcripts",
"Sustainability",
"Corporate governance",
"eng",
"license:apache-2.... | text-classification | soleimanian | null | null | soleimanian/financial-roberta-large-sentiment | 29 | 21,345 | transformers | 2022-05-16T04:09:10 | ---
license: apache-2.0
language:
- eng
tags:
- text-classification
- Sentiment
- RoBERTa
- Financial Statements
- Accounting
- Finance
- Business
- ESG
- CSR Reports
- Financial News
- Earnings Call Transcripts
- Sustainability
- Corporate governance
---
<!DOCTYPE html>
<html>
<body>
<h1><b>Financial-RoBERTa</b></... | 2,193 | [
[
-0.01529693603515625,
-0.058929443359375,
0.0157928466796875,
0.039794921875,
-0.0131378173828125,
-0.0010786056518554688,
-0.01464080810546875,
-0.0210113525390625,
0.034210205078125,
0.0316162109375,
-0.060821533203125,
-0.056060791015625,
-0.054443359375,
... |
beomi/llama-2-ko-7b | 2023-11-03T05:15:01.000Z | [
"transformers",
"pytorch",
"safetensors",
"llama",
"text-generation",
"facebook",
"meta",
"llama-2",
"kollama",
"llama-2-ko",
"en",
"ko",
"doi:10.57967/hf/1098",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | beomi | null | null | beomi/llama-2-ko-7b | 93 | 21,343 | transformers | 2023-07-20T03:25:25 | ---
language:
- en
- ko
pipeline_tag: text-generation
inference: false
tags:
- facebook
- meta
- pytorch
- llama
- llama-2
- kollama
- llama-2-ko
---
> 🚧 Note: this repo is under construction 🚧
**Update Log**
- 2023.10.19
- Fix Tokenizer bug(space not applied when decoding) after `transforemrs>=4.34.0`
# **Lla... | 8,714 | [
[
-0.0477294921875,
-0.04254150390625,
0.01678466796875,
0.0357666015625,
-0.047637939453125,
0.01207733154296875,
-0.0007572174072265625,
-0.04901123046875,
0.06610107421875,
0.01239776611328125,
-0.046875,
-0.05047607421875,
-0.047454833984375,
0.01663208007... |
22h/vintedois-diffusion-v0-1 | 2022-12-30T17:58:36.000Z | [
"diffusers",
"text-to-image",
"license:creativeml-openrail-m",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | 22h | null | null | 22h/vintedois-diffusion-v0-1 | 382 | 21,169 | diffusers | 2022-12-27T13:45:40 | ---
license: creativeml-openrail-m
tags:
- text-to-image
---
### Vintedois (22h) Diffusion model trained by [Predogl](https://twitter.com/Predogl) and [piEsposito](https://twitter.com/piesposi_to) with open weights, configs and prompts (as it should be)
This model was trained on a large amount of high quality images w... | 3,954 | [
[
-0.052642822265625,
-0.0595703125,
0.041748046875,
0.039794921875,
-0.022979736328125,
-0.017333984375,
0.004100799560546875,
-0.038299560546875,
0.05181884765625,
0.0280914306640625,
-0.054351806640625,
-0.042938232421875,
-0.038116455078125,
-0.00067806243... |
google/mobilenet_v2_1.0_224 | 2023-10-31T13:40:16.000Z | [
"transformers",
"pytorch",
"safetensors",
"mobilenet_v2",
"image-classification",
"vision",
"dataset:imagenet-1k",
"arxiv:1801.04381",
"license:other",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | image-classification | google | null | null | google/mobilenet_v2_1.0_224 | 6 | 21,167 | transformers | 2022-11-10T16:04:32 | ---
license: other
tags:
- vision
- image-classification
datasets:
- imagenet-1k
widget:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg
example_title: Tiger
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg
example_title: Teapot
- src: https://hu... | 3,315 | [
[
-0.033905029296875,
-0.016387939453125,
-0.0189361572265625,
-0.004421234130859375,
-0.0233154296875,
-0.026763916015625,
0.0195770263671875,
-0.0552978515625,
0.026031494140625,
0.0307159423828125,
-0.0235137939453125,
-0.01132965087890625,
-0.044281005859375,
... |
Yntec/YiffyMix | 2023-10-24T16:53:11.000Z | [
"diffusers",
"Base Model",
"General",
"Furry",
"chilon249",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"license:creativeml-openrail-m",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"region:us",
"has_space"
] | text-to-image | Yntec | null | null | Yntec/YiffyMix | 5 | 21,163 | diffusers | 2023-10-24T15:33:52 | ---
license: creativeml-openrail-m
library_name: diffusers
pipeline_tag: text-to-image
tags:
- Base Model
- General
- Furry
- chilon249
- stable-diffusion
- stable-diffusion-diffusers
- diffusers
- text-to-image
---
# YiffyMix v31
This model with the MoistMixV2 VAE baked in.
Comparison:
![Comparison](https://cdn-up... | 935 | [
[
-0.01390838623046875,
-0.0198974609375,
0.028778076171875,
0.00696563720703125,
-0.0309600830078125,
-0.01161956787109375,
0.0308990478515625,
-0.014923095703125,
0.043701171875,
0.0648193359375,
-0.044189453125,
-0.0205230712890625,
-0.033203125,
-0.0134277... |
microsoft/wavlm-base | 2021-12-22T17:23:36.000Z | [
"transformers",
"pytorch",
"wavlm",
"feature-extraction",
"speech",
"en",
"arxiv:2110.13900",
"has_space",
"region:us"
] | feature-extraction | microsoft | null | null | microsoft/wavlm-base | 1 | 21,157 | transformers | 2022-03-02T23:29:05 | ---
language:
- en
datasets:
tags:
- speech
inference: false
---
# WavLM-Base
[Microsoft's WavLM](https://github.com/microsoft/unilm/tree/master/wavlm)
The base model pretrained on 16kHz sampled speech audio. When using the model, make sure that your speech input is also sampled at 16kHz.
**Note**: This model does... | 3,774 | [
[
-0.0250091552734375,
-0.048309326171875,
0.00469207763671875,
0.01024627685546875,
-0.0182647705078125,
-0.005725860595703125,
-0.0134124755859375,
-0.0482177734375,
-0.0100860595703125,
0.031280517578125,
-0.04656982421875,
-0.042022705078125,
-0.039306640625,
... |
optimum/distilbert-base-uncased-finetuned-sst-2-english | 2022-06-13T13:43:16.000Z | [
"transformers",
"onnx",
"text-classification",
"en",
"dataset:sst2",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-classification | optimum | null | null | optimum/distilbert-base-uncased-finetuned-sst-2-english | 2 | 21,116 | transformers | 2022-03-24T16:06:17 | ---
language: en
license: apache-2.0
datasets:
- sst2
---
# ONNX convert DistilBERT base uncased finetuned SST-2
## Conversion of [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english)
This model is a fine-tune checkpoint of [DistilBERT-base-uncased]... | 2,053 | [
[
-0.02056884765625,
-0.05096435546875,
0.023406982421875,
0.0213470458984375,
-0.037567138671875,
-0.0119476318359375,
-0.01409149169921875,
-0.0252532958984375,
0.0029506683349609375,
0.0364990234375,
-0.043182373046875,
-0.038970947265625,
-0.06011962890625,
... |
GanymedeNil/text2vec-large-chinese | 2023-08-05T02:28:03.000Z | [
"transformers",
"pytorch",
"safetensors",
"bert",
"feature-extraction",
"text2vec",
"sentence-similarity",
"zh",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | sentence-similarity | GanymedeNil | null | null | GanymedeNil/text2vec-large-chinese | 638 | 21,112 | transformers | 2023-03-07T03:32:14 | ---
license: apache-2.0
language:
- zh
pipeline_tag: sentence-similarity
tags:
- text2vec
- feature-extraction
- sentence-similarity
- transformers
---
Based on the derivative model of https://huggingface.co/shibing624/text2vec-base-chinese, replace MacBERT with LERT, and keep other training conditions unchanged。
Ref... | 441 | [
[
0.003429412841796875,
-0.056304931640625,
0.0262298583984375,
0.01003265380859375,
-0.0224151611328125,
-0.0073089599609375,
-0.0086212158203125,
-0.043548583984375,
0.0203704833984375,
0.053680419921875,
-0.044189453125,
-0.032623291015625,
-0.0528564453125,
... |
TheBloke/WizardLM-Uncensored-Falcon-7B-GPTQ | 2023-08-21T10:28:42.000Z | [
"transformers",
"safetensors",
"RefinedWebModel",
"text-generation",
"custom_code",
"license:apache-2.0",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | TheBloke | null | null | TheBloke/WizardLM-Uncensored-Falcon-7B-GPTQ | 46 | 21,080 | transformers | 2023-06-01T17:21:40 | ---
license: apache-2.0
---
<!-- header start -->
<!-- 200823 -->
<div style="width: auto; margin-left: auto; margin-right: auto">
<img src="https://i.imgur.com/EBdldam.jpg" alt="TheBlokeAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</div>
<div style="display: flex; justify-content: space-be... | 9,908 | [
[
-0.04302978515625,
-0.06011962890625,
0.0149383544921875,
0.01386260986328125,
-0.0136566162109375,
0.005207061767578125,
0.0170745849609375,
-0.034637451171875,
0.0299224853515625,
0.0141754150390625,
-0.047210693359375,
-0.0307159423828125,
-0.03692626953125,
... |
facebook/wav2vec2-conformer-rel-pos-large | 2022-12-07T14:01:31.000Z | [
"transformers",
"pytorch",
"wav2vec2-conformer",
"pretraining",
"speech",
"en",
"dataset:librispeech_asr",
"arxiv:2010.05171",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | facebook | null | null | facebook/wav2vec2-conformer-rel-pos-large | 7 | 21,008 | transformers | 2022-04-17T15:54:03 | ---
language: en
datasets:
- librispeech_asr
tags:
- speech
license: apache-2.0
---
# Wav2Vec2-Conformer-Large with Relative Position Embeddings
Wav2Vec2 Conformer with relative position embeddings, pretrained on 960 hours of Librispeech on 16kHz sampled speech audio. When using the model make sure that your speech i... | 1,329 | [
[
0.002262115478515625,
-0.030670166015625,
0.0234222412109375,
0.0034046173095703125,
-0.015655517578125,
-0.036590576171875,
-0.0170440673828125,
-0.0526123046875,
-0.0229949951171875,
0.0194244384765625,
-0.03643798828125,
-0.0312347412109375,
-0.05728149414062... |
facebook/maskformer-swin-base-coco | 2022-11-10T10:05:16.000Z | [
"transformers",
"pytorch",
"maskformer",
"vision",
"image-segmentation",
"dataset:coco",
"arxiv:2107.06278",
"license:other",
"endpoints_compatible",
"has_space",
"region:us"
] | image-segmentation | facebook | null | null | facebook/maskformer-swin-base-coco | 9 | 21,007 | transformers | 2022-03-02T23:29:05 | ---
license: other
tags:
- vision
- image-segmentation
datasets:
- coco
widget:
- src: http://images.cocodataset.org/val2017/000000039769.jpg
example_title: Cats
- src: http://images.cocodataset.org/val2017/000000039770.jpg
example_title: Castle
---
# MaskFormer
MaskFormer model trained on COCO panoptic segmentat... | 2,775 | [
[
-0.049957275390625,
-0.056304931640625,
0.0166168212890625,
0.0288238525390625,
-0.020782470703125,
-0.0134735107421875,
0.005390167236328125,
-0.0472412109375,
0.03314208984375,
0.052276611328125,
-0.061279296875,
-0.043212890625,
-0.059417724609375,
-0.016... |
facebook/opt-30b | 2023-01-24T17:10:35.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"opt",
"text-generation",
"en",
"arxiv:2205.01068",
"arxiv:2005.14165",
"license:other",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | facebook | null | null | facebook/opt-30b | 132 | 20,997 | transformers | 2022-05-11T08:27:14 | ---
language: en
inference: false
tags:
- text-generation
- opt
license: other
commercial: false
---
# OPT : Open Pre-trained Transformer Language Models
OPT was first introduced in [Open Pre-trained Transformer Language Models](https://arxiv.org/abs/2205.01068) and first released in [metaseq's repository](https://g... | 10,010 | [
[
-0.0228271484375,
-0.06365966796875,
0.0130767822265625,
0.0190582275390625,
-0.01221466064453125,
-0.01116180419921875,
-0.032745361328125,
-0.03289794921875,
0.004150390625,
0.033538818359375,
-0.045257568359375,
-0.032379150390625,
-0.0465087890625,
0.007... |
vinid/plip | 2023-03-31T02:46:21.000Z | [
"transformers",
"pytorch",
"clip",
"zero-shot-image-classification",
"endpoints_compatible",
"has_space",
"region:us"
] | zero-shot-image-classification | vinid | null | null | vinid/plip | 19 | 20,915 | transformers | 2023-03-04T19:37:10 | ---
{}
---
## Model Use (from [CLIP Model Card](https://huggingface.co/openai/clip-vit-large-patch14))
### Intended Use
The model is intended as a research output for research communities. We hope that this model will enable researchers to better understand and explore zero-shot, arbitrary image classification. We a... | 3,114 | [
[
-0.0175628662109375,
-0.052093505859375,
0.03802490234375,
0.030426025390625,
-0.0498046875,
-0.0140380859375,
0.006343841552734375,
-0.04669189453125,
0.0401611328125,
0.033966064453125,
-0.03515625,
-0.06036376953125,
-0.057464599609375,
0.0069808959960937... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.