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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Recognai/bert-base-spanish-wwm-cased-xnli | 2023-07-14T22:22:51.000Z | [
"transformers",
"pytorch",
"jax",
"safetensors",
"bert",
"text-classification",
"zero-shot-classification",
"nli",
"es",
"dataset:xnli",
"license:mit",
"endpoints_compatible",
"has_space",
"region:us"
] | zero-shot-classification | Recognai | null | null | Recognai/bert-base-spanish-wwm-cased-xnli | 14 | 11,297 | transformers | 2022-03-02T23:29:04 | ---
language: es
tags:
- zero-shot-classification
- nli
- pytorch
datasets:
- xnli
license: mit
pipeline_tag: zero-shot-classification
widget:
- text: "El autor se perfila, a los 50 años de su muerte, como uno de los grandes de su siglo"
candidate_labels: "cultura, sociedad, economia, salud, deportes"
---
# bert-bas... | 2,081 | [
[
-0.022857666015625,
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0.03460693359375,
0.017486572265625,
-0.044525146484375,
-0.056640625,
-0.04400634765625,
-0.0... |
LeoLM/leo-hessianai-7b-chat | 2023-10-09T21:30:55.000Z | [
"transformers",
"pytorch",
"llama",
"text-generation",
"custom_code",
"en",
"de",
"dataset:LeoLM/OpenSchnabeltier",
"dataset:OpenAssistant/OASST-DE",
"dataset:FreedomIntelligence/alpaca-gpt4-deutsch",
"dataset:FreedomIntelligence/evol-instruct-deutsch",
"dataset:LeoLM/German_Poems",
"dataset... | text-generation | LeoLM | null | null | LeoLM/leo-hessianai-7b-chat | 10 | 11,296 | transformers | 2023-09-10T18:26:13 | ---
datasets:
- LeoLM/OpenSchnabeltier
- OpenAssistant/OASST-DE
- FreedomIntelligence/alpaca-gpt4-deutsch
- FreedomIntelligence/evol-instruct-deutsch
- LeoLM/German_Poems
- LeoLM/German_Songs
language:
- en
- de
library_name: transformers
pipeline_tag: text-generation
---
# LAION LeoLM: **L**inguistically **E**nhanced ... | 8,055 | [
[
-0.02740478515625,
-0.056640625,
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0.03448486328125,
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0.0182037353515625,
-0.04736328125,
-0.054290771484375,
-0.04595947265625,
0.00984954833... |
cerebras/Cerebras-GPT-111M | 2023-04-07T13:48:17.000Z | [
"transformers",
"pytorch",
"gpt2",
"causal-lm",
"text-generation",
"en",
"dataset:the_pile",
"arxiv:2304.03208",
"arxiv:2203.15556",
"arxiv:2101.00027",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | cerebras | null | null | cerebras/Cerebras-GPT-111M | 65 | 11,280 | transformers | 2023-03-17T00:02:47 | ---
language:
- en
tags:
- pytorch
- causal-lm
license: apache-2.0
datasets:
- the_pile
pipeline_tag: text-generation
---
# Cerebras-GPT 111M
Check out our [Blog Post](https://www.cerebras.net/cerebras-gpt) and [arXiv paper](https://arxiv.org/abs/2304.03208)!
## Model Description
The Cerebras-GPT family is released ... | 12,558 | [
[
-0.0281982421875,
-0.046539306640625,
0.019500732421875,
0.01294708251953125,
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0.0138397216796875,
0.02093505859375,
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-0.031646728515625,
-0.055816650390625,
... |
flax-sentence-embeddings/all_datasets_v4_MiniLM-L6 | 2021-07-23T15:49:28.000Z | [
"sentence-transformers",
"pytorch",
"bert",
"feature-extraction",
"sentence-similarity",
"en",
"arxiv:2104.08727",
"arxiv:1810.09305",
"arxiv:2102.07033",
"arxiv:1904.06472",
"endpoints_compatible",
"has_space",
"region:us"
] | sentence-similarity | flax-sentence-embeddings | null | null | flax-sentence-embeddings/all_datasets_v4_MiniLM-L6 | 27 | 11,264 | sentence-transformers | 2022-03-02T23:29:05 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
language: en
---
# Model description
The project aims to train sentence embedding models on very large sentence level datasets using a self-supervised
contrastive learning objective. We used the pretrained ... | 7,333 | [
[
-0.0298309326171875,
-0.0592041015625,
0.023681640625,
-0.0031223297119140625,
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-0.018585205078125,
-0.031005859375,
0.0341796875,
0.018829345703125,
-0.041046142578125,
-0.0399169921875,
-0.03668212890625,
0.01670... |
facebook/rag-sequence-base | 2020-12-11T21:39:37.000Z | [
"transformers",
"pytorch",
"rag",
"arxiv:2005.11401",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | facebook | null | null | facebook/rag-sequence-base | 4 | 11,261 | transformers | 2022-03-02T23:29:05 | ---
license: apache-2.0
thumbnail: https://huggingface.co/front/thumbnails/facebook.png
---
## RAG
This is a non-finetuned version of the RAG-Sequence 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, Aleksand... | 2,377 | [
[
-0.025634765625,
-0.052154541015625,
0.0008821487426757812,
0.0037899017333984375,
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-0.007648468017578125,
-0.00945281982421875,
0.02301025390625,
0.038330078125,
-0.038055419921875,
0.00585174560546875,
-0.0467834472656... |
chargoddard/platypus-2-22b-relora | 2023-08-18T08:05:29.000Z | [
"transformers",
"safetensors",
"llama",
"text-generation",
"en",
"dataset:chargoddard/Open-Platypus-Chat",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | chargoddard | null | null | chargoddard/platypus-2-22b-relora | 0 | 11,250 | transformers | 2023-08-17T04:22:40 | ---
datasets:
- chargoddard/Open-Platypus-Chat
language:
- en
tags:
- llama
---
Experimental ReLoRA-trained model using the OpenPlatypus dataset. Ran for one epoch, with three lora restarts.
Not recommended for use yet. Mostly tossing this up for testing.
Base model was [llama2-22b-blocktriangular](https://huggingfac... | 1,039 | [
[
-0.0242767333984375,
-0.054290771484375,
0.0216522216796875,
0.0235595703125,
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0.0301513671875,
0.018798828125,
-0.07232666015625,
-0.037506103515625,
-0.0091400146484375,
0.0054... |
facebook/flava-full | 2023-09-25T09:37:12.000Z | [
"transformers",
"pytorch",
"flava",
"pretraining",
"arxiv:2112.04482",
"arxiv:2108.10904",
"license:bsd-3-clause",
"endpoints_compatible",
"has_space",
"region:us"
] | null | facebook | null | null | facebook/flava-full | 18 | 11,248 | transformers | 2022-04-09T00:40:12 | ---
license: bsd-3-clause
---
## Model Card: FLAVA
## Model Details
FLAVA model was developed by the researchers at FAIR to understand if a single model can work across different modalities with a unified architecture. The model was pretrained solely using publicly available multimodal datasets containing 70M image-t... | 11,869 | [
[
-0.037841796875,
-0.07470703125,
0.001972198486328125,
0.02435302734375,
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0.02716064453125,
0.017791748046875,
-0.0355224609375,
-0.0133209228515625,
-0.0421142578125,
-0.0037193... |
lgaalves/gpt2-dolly | 2023-10-06T21:38:49.000Z | [
"transformers",
"pytorch",
"safetensors",
"gpt2",
"text-generation",
"en",
"dataset:databricks/databricks-dolly-15k",
"license:mit",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | lgaalves | null | null | lgaalves/gpt2-dolly | 1 | 11,228 | transformers | 2023-08-04T21:54:24 | ---
license: mit
datasets:
- databricks/databricks-dolly-15k
language:
- en
pipeline_tag: text-generation
---
# GPT-2-dolly
**GPT-2-dolly** is an instruction fine-tuned model based on the GPT-2 transformer architecture.
### Benchmark Metrics
| Metric | GPT-2-dolly | GPT-2 (base) |
|---------------... | 2,255 | [
[
-0.014251708984375,
-0.0804443359375,
0.0090484619140625,
0.0188446044921875,
-0.015899658203125,
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-0.02703857421875,
-0.004451751708984375,
0.0302886962890625,
-0.035858154296875,
-0.020965576171875,
-0.06427001953125,... |
openbmb/UltraRM-13b | 2023-10-14T09:49:47.000Z | [
"transformers",
"pytorch",
"llama",
"dataset:openbmb/UltraFeedback",
"arxiv:2310.01377",
"license:mit",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | openbmb | null | null | openbmb/UltraRM-13b | 26 | 11,228 | transformers | 2023-09-22T09:34:58 | ---
license: mit
datasets:
- openbmb/UltraFeedback
---
# News
- [2023/09/26]: UltraRM unleashes the power of [UltraLM-13B-v2.0](https://huggingface.co/openbmb/UltraLM-13b-v2.0) and [UltraLM-13B](https://huggingface.co/openbmb/UltraLM-13b)! A simple best-of-16 sampling achieves **92.30%** (UltraLM2, 🥇 in 13B results)... | 6,178 | [
[
-0.02764892578125,
-0.041107177734375,
0.0233612060546875,
0.01247406005859375,
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0.0021038055419921875,
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0.04937744140625,
0.029266357421875,
-0.04241943359375,
-0.0282440185546875,
-0.02276611328125,
... |
chargoddard/llama2-22b-blocktriangular | 2023-08-19T01:44:21.000Z | [
"transformers",
"pytorch",
"llama",
"text-generation",
"llama2",
"dataset:togethercomputer/RedPajama-Data-1T-Sample",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | chargoddard | null | null | chargoddard/llama2-22b-blocktriangular | 4 | 11,210 | transformers | 2023-07-25T07:11:44 | ---
datasets:
- togethercomputer/RedPajama-Data-1T-Sample
tags:
- llama2
- llama
---
Similar to llama2-22b, but with BLOCK_DIAGONAL=false in the merge and twice the fine-tuning tokens.
Again, not intended for direct use - meant as a base for further tuning and merging. | 272 | [
[
-0.036529541015625,
-0.05145263671875,
-0.0009059906005859375,
0.061767578125,
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0.0330810546875,
0.052703857421875,
-0.058013916015625,
-0.04180908203125,
-0.031646728515625,
-0.... |
nitrosocke/Ghibli-Diffusion | 2023-08-03T19:46:59.000Z | [
"diffusers",
"stable-diffusion",
"text-to-image",
"image-to-image",
"en",
"license:creativeml-openrail-m",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | nitrosocke | null | null | nitrosocke/Ghibli-Diffusion | 566 | 11,198 | diffusers | 2022-11-18T15:50:51 | ---
language:
- en
license: creativeml-openrail-m
thumbnail: "https://huggingface.co/nitrosocke/Ghibli-Diffusion/resolve/main/images/ghibli-diffusion-thumbnail.jpg"
tags:
- stable-diffusion
- text-to-image
- image-to-image
- diffusers
---
### Ghibli Diffusion
This is the fine-tuned Stable Diffusion model trained on i... | 4,074 | [
[
-0.041961669921875,
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0.0290679931640625,
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0.0002180337905883789,
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0.024261474609375,
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-0.035888671875,
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-0.02764... |
51la5/roberta-large-NER | 2022-10-17T08:36:02.000Z | [
"transformers",
"pytorch",
"rust",
"xlm-roberta",
"token-classification",
"multilingual",
"af",
"am",
"ar",
"as",
"az",
"be",
"bg",
"bn",
"br",
"bs",
"ca",
"cs",
"cy",
"da",
"de",
"el",
"en",
"eo",
"es",
"et",
"eu",
"fa",
"fi",
"fr",
"fy",
"ga",
"gd",
... | token-classification | 51la5 | null | null | 51la5/roberta-large-NER | 25 | 11,195 | transformers | 2022-10-17T08:25:02 | ---
language:
- multilingual
- af
- am
- ar
- as
- az
- be
- bg
- bn
- br
- bs
- ca
- cs
- cy
- da
- de
- el
- en
- eo
- es
- et
- eu
- fa
- fi
- fr
- fy
- ga
- gd
- gl
- gu
- ha
- he
- hi
- hr
- hu
- hy
- id
- is
- it
- ja
- jv
- ka
- kk
- km
- kn
- ko
- ku
- ky
- la
- lo
- lt
- lv
- mg
- mk
- ml
- mn
- mr
- ms
- my
... | 7,668 | [
[
-0.0274810791015625,
-0.0413818359375,
0.01332855224609375,
0.00640869140625,
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0.0114898681640625,
0.034759521484375,
-0.031097412109375,
-0.044586181640625,
-0.0584716796875,
0... |
Open-Orca/Mistral-7B-SlimOrca | 2023-10-14T04:40:06.000Z | [
"transformers",
"pytorch",
"mistral",
"text-generation",
"en",
"dataset:Open-Orca/SlimOrca",
"arxiv:2306.02707",
"arxiv:2301.13688",
"license:apache-2.0",
"endpoints_compatible",
"text-generation-inference",
"region:us",
"has_space"
] | text-generation | Open-Orca | null | null | Open-Orca/Mistral-7B-SlimOrca | 10 | 11,195 | transformers | 2023-10-08T17:42:56 | ---
datasets:
- Open-Orca/SlimOrca
language:
- en
library_name: transformers
pipeline_tag: text-generation
license: apache-2.0
---
<p><h1>🐋 Mistral-7B-SlimOrca 🐋</h1></p>
PRE-RELEASE, DEMO MODEL
![OpenOrca Logo](https://huggingface.co/Open-Orca/Mistral-7B-OpenOrca/resolve/main/Images/MistralOrcaLogo.png "Mistral... | 7,057 | [
[
-0.02874755859375,
-0.057281494140625,
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0.00372314453125,
-0.005706787109375,
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0.0133056640625,
0.01204681396484375,
-0.034942626953125,
-0.039703369140625,
-0.0309906005859375,
... |
flair/ner-multi | 2023-04-05T10:25:41.000Z | [
"flair",
"pytorch",
"token-classification",
"sequence-tagger-model",
"en",
"de",
"nl",
"es",
"multilingual",
"dataset:conll2003",
"region:us"
] | token-classification | flair | null | null | flair/ner-multi | 8 | 11,192 | flair | 2022-03-02T23:29:05 | ---
tags:
- flair
- token-classification
- sequence-tagger-model
language:
- en
- de
- nl
- es
- multilingual
datasets:
- conll2003
widget:
- text: "George Washington ging nach Washington"
---
## 4-Language NER in Flair (English, German, Dutch and Spanish)
This is the standard 4-class NER model for 4 CoNLL-03 lan... | 4,174 | [
[
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-0.046905517578125,
0.006755828857421875,
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0.035369873046875,
0.0190582275390625,
-0.0399169921875,
-0.04559326171875,
-0.030364990234375,
... |
jphme/em_german_leo_mistral | 2023-10-27T23:50:35.000Z | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"pytorch",
"german",
"deutsch",
"leolm",
"de",
"license:apache-2.0",
"text-generation-inference",
"region:us"
] | text-generation | jphme | null | null | jphme/em_german_leo_mistral | 23 | 11,191 | transformers | 2023-10-07T10:02:26 | ---
inference: false
language:
- de
library_name: transformers
license: apache-2.0
model_creator: jphme
model_name: EM German
model_type: mistral
pipeline_tag: text-generation
prompt_template: 'Du bist ein hilfreicher Assistent. USER: Was ist 1+1? ASSISTANT:'
tags:
- pytorch
- german
- deutsch
- mistral
- leolm
---
![E... | 9,605 | [
[
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0.01... |
bhenrym14/airoboros-33b-gpt4-1.4.1-lxctx-PI-16384-fp16 | 2023-08-14T20:23:25.000Z | [
"transformers",
"safetensors",
"llama",
"text-generation",
"dataset:jondurbin/airoboros-gpt4-1.4.1",
"arxiv:2306.15595",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | bhenrym14 | null | null | bhenrym14/airoboros-33b-gpt4-1.4.1-lxctx-PI-16384-fp16 | 4 | 11,179 | transformers | 2023-07-13T20:01:51 | ---
datasets:
- jondurbin/airoboros-gpt4-1.4.1
---
**UPDATE 8/14: I have changed the `config.json` to include the appropriate RoPE scaling specification. This model should now work with the new `Transformers` without applying any patches.**
Find GPTQ quantized weights here: https://huggingface.co/bhenrym14/airoboros-... | 13,681 | [
[
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-0.0225982666015625,
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... |
lgaalves/gpt2_camel_physics-platypus | 2023-10-10T02:31:09.000Z | [
"transformers",
"pytorch",
"safetensors",
"gpt2",
"text-generation",
"en",
"dataset:garage-bAInd/Open-Platypus",
"dataset:lgaalves/camel-ai-physics",
"license:mit",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | lgaalves | null | null | lgaalves/gpt2_camel_physics-platypus | 0 | 11,159 | transformers | 2023-09-05T21:39:00 | ---
license: mit
datasets:
- garage-bAInd/Open-Platypus
- lgaalves/camel-ai-physics
language:
- en
pipeline_tag: text-generation
---
# lgaalves/gpt2_camel_physics-platypus
**lgaalves/gpt2_camel_physics-platypuss** is an instruction fine-tuned model based on the GPT-2 transformer architecture.
### Benchmark Metric... | 2,495 | [
[
-0.02178955078125,
-0.066162109375,
0.0117950439453125,
0.01715087890625,
-0.0209808349609375,
-0.00482940673828125,
-0.0283660888671875,
-0.035064697265625,
0.0017118453979492188,
0.01474761962890625,
-0.040008544921875,
-0.0280303955078125,
-0.04656982421875,
... |
garage-bAInd/Platypus-30B | 2023-07-25T02:35:57.000Z | [
"transformers",
"pytorch",
"llama",
"text-generation",
"en",
"license:other",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | garage-bAInd | null | null | garage-bAInd/Platypus-30B | 16 | 11,158 | transformers | 2023-06-19T23:17:50 | ---
language:
- en
tags:
- llama
license: other
metrics:
- MMLU
- ARC
- HellaSwag
- TruthfulQA
---
# 🥳 Platypus-30B has arrived!
Platypus-30B is an instruction fine-tuned model based on the LLaMA-30B transformer architecture.
| Metric | Value |
|-----------------------|-------|
| MMLU (5-shot) ... | 4,044 | [
[
-0.0195465087890625,
-0.06256103515625,
0.0247955322265625,
0.032623291015625,
-0.01995849609375,
-0.0073089599609375,
-0.027374267578125,
-0.0276947021484375,
0.004581451416015625,
0.026336669921875,
-0.041259765625,
-0.0390625,
-0.047271728515625,
0.003461... |
baichuan-inc/Baichuan-13B-Chat | 2023-09-01T03:35:56.000Z | [
"transformers",
"pytorch",
"baichuan",
"text-generation",
"custom_code",
"zh",
"en",
"arxiv:2104.09864",
"arxiv:2108.12409",
"arxiv:2009.03300",
"endpoints_compatible",
"has_space",
"region:us"
] | text-generation | baichuan-inc | null | null | baichuan-inc/Baichuan-13B-Chat | 607 | 11,142 | transformers | 2023-07-08T05:58:27 | ---
language:
- zh
- en
pipeline_tag: text-generation
inference: false
---
# Baichuan-13B-Chat
<!-- Provide a quick summary of what the model is/does. -->
## 介绍
Baichuan-13B-Chat为Baichuan-13B系列模型中对齐后的版本，预训练模型可见[Baichuan-13B-Base](https://huggingface.co/baichuan-inc/Baichuan-13B-Base)。
[Baichuan-13B](https://github.c... | 13,995 | [
[
-0.0221099853515625,
-0.057281494140625,
0.0024280548095703125,
0.040985107421875,
-0.026123046875,
-0.0201416015625,
-0.018402099609375,
-0.0323486328125,
0.00670623779296875,
0.0160675048828125,
-0.033477783203125,
-0.03912353515625,
-0.044647216796875,
-0... |
jondurbin/airoboros-33b-gpt4-2.0 | 2023-08-04T20:54:16.000Z | [
"transformers",
"pytorch",
"llama",
"text-generation",
"dataset:jondurbin/airoboros-gpt4-m2.0",
"license:cc-by-nc-4.0",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | jondurbin | null | null | jondurbin/airoboros-33b-gpt4-2.0 | 4 | 11,140 | transformers | 2023-07-29T07:53:46 | ---
license: cc-by-nc-4.0
datasets:
- jondurbin/airoboros-gpt4-m2.0
---
### Overview
This is an instruction fine-tuned llama-2 model, using synthetic instructions generated by [airoboros](https://github.com/jondurbin/airoboros)
- The 2.0 series are generated exclusively from 0614 version of gpt-4, as mechanism to co... | 17,082 | [
[
-0.0296478271484375,
-0.06591796875,
0.039398193359375,
0.0201416015625,
-0.01136016845703125,
-0.014739990234375,
-0.009918212890625,
-0.0238494873046875,
0.0162506103515625,
0.0262298583984375,
-0.054595947265625,
-0.042388916015625,
-0.03277587890625,
0.0... |
Yntec/animeSEXTILLION | 2023-09-21T23:01:06.000Z | [
"diffusers",
"Anime",
"Chibi",
"General",
"realisticElves",
"text-to-image",
"stable-diffusion",
"stable-diffusion-diffusers",
"license:creativeml-openrail-m",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | Yntec | null | null | Yntec/animeSEXTILLION | 1 | 11,140 | diffusers | 2023-09-21T20:29:18 | ---
license: creativeml-openrail-m
library_name: diffusers
pipeline_tag: text-to-image
tags:
- Anime
- Chibi
- General
- realisticElves
- text-to-image
- stable-diffusion
- stable-diffusion-diffusers
- diffusers
---
# anime SEXTILLION
A mix of animeTWO and animeTEN, both by realisticElves, to bring my favorite thing... | 1,339 | [
[
-0.042236328125,
-0.035980224609375,
0.034576416015625,
0.044342041015625,
-0.015838623046875,
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0.0125732421875,
-0.018951416015625,
0.0633544921875,
0.0452880859375,
-0.07122802734375,
-0.0234527587890625,
-0.025177001953125,
-0.01091... |
openchat/openchat_v3.2 | 2023-09-24T10:10:37.000Z | [
"transformers",
"pytorch",
"llama",
"text-generation",
"arxiv:2309.11235",
"license:llama2",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | openchat | null | null | openchat/openchat_v3.2 | 39 | 11,121 | transformers | 2023-07-30T10:12:00 | ---
license: llama2
---
# OpenChat: Advancing Open-source Language Models with Imperfect Data</h1>
<div align="center">
<img src="https://raw.githubusercontent.com/imoneoi/openchat/master/assets/logo_new.png" style="width: 65%">
</div>
[OpenChat](https://github.com/imoneoi/openchat) is a series of open-source lang... | 8,931 | [
[
-0.0472412109375,
-0.06597900390625,
0.0236053466796875,
0.032745361328125,
-0.01543426513671875,
-0.01110076904296875,
-0.021148681640625,
-0.039581298828125,
0.023956298828125,
0.027679443359375,
-0.043701171875,
-0.032928466796875,
-0.033538818359375,
-0.... |
Yntec/sexyToons | 2023-08-04T04:24:16.000Z | [
"diffusers",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"alexds9",
"license:creativeml-openrail-m",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | Yntec | null | null | Yntec/sexyToons | 6 | 11,107 | diffusers | 2023-07-27T09:52:16 | ---
license: creativeml-openrail-m
library_name: diffusers
pipeline_tag: text-to-image
tags:
- stable-diffusion
- stable-diffusion-diffusers
- diffusers
- text-to-image
- alexds9
---
# Sexy Toons feat. Pipa
Original pages:
https://civitai.com/models/35549/sexy-toons-feat-pipa | 280 | [
[
-0.03009033203125,
-0.016876220703125,
0.0179290771484375,
0.036773681640625,
-0.033203125,
-0.03753662109375,
0.0283966064453125,
0.001556396484375,
0.086181640625,
0.0921630859375,
-0.0638427734375,
-0.0215606689453125,
-0.01959228515625,
-0.00737380981445... |
m3hrdadfi/wav2vec2-large-xlsr-persian-v3 | 2021-11-04T15:22:11.000Z | [
"transformers",
"pytorch",
"tf",
"wav2vec2",
"automatic-speech-recognition",
"audio",
"speech",
"xlsr-fine-tuning-week",
"fa",
"dataset:common_voice",
"model-index",
"endpoints_compatible",
"has_space",
"region:us"
] | automatic-speech-recognition | m3hrdadfi | null | null | m3hrdadfi/wav2vec2-large-xlsr-persian-v3 | 18 | 11,102 | transformers | 2022-03-02T23:29:05 | ---
language: fa
datasets:
- common_voice
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
widget:
- example_title: Common Voice sample 1
src: https://huggingface.co/m3hrdadfi/wav2vec2-large-xlsr-persian-v3/resolve/main/sample1.flac
- example_title: Common Voice sample 2978
src: https:/... | 7,249 | [
[
-0.04754638671875,
-0.0428466796875,
0.01250457763671875,
0.0166015625,
-0.0307159423828125,
-0.0140380859375,
-0.025726318359375,
-0.036224365234375,
0.0245361328125,
0.0233306884765625,
-0.0418701171875,
-0.03369140625,
-0.050201416015625,
0.00383758544921... |
uukuguy/speechless-llama2-13b | 2023-10-13T09:16:15.000Z | [
"transformers",
"safetensors",
"llama",
"text-generation",
"facebook",
"meta",
"pytorch",
"llama-2",
"en",
"dataset:Open-Orca/OpenOrca",
"dataset:garage-bAInd/Open-Platypus",
"dataset:WizardLM/WizardLM_evol_instruct_V2_196k",
"arxiv:2307.09288",
"has_space",
"text-generation-inference",
... | text-generation | uukuguy | null | null | uukuguy/speechless-llama2-13b | 3 | 11,102 | transformers | 2023-09-02T00:57:00 | ---
extra_gated_heading: Access Llama 2 on Hugging Face
extra_gated_description: >-
This is a form to enable access to Llama 2 on Hugging Face after you have been
granted access from Meta. Please visit the [Meta website](https://ai.meta.com/resources/models-and-libraries/llama-downloads) and accept our
license te... | 11,175 | [
[
-0.0179443359375,
-0.0572509765625,
0.02960205078125,
0.01477813720703125,
-0.0259857177734375,
0.01605224609375,
-0.00604248046875,
-0.0535888671875,
0.003208160400390625,
0.020172119140625,
-0.054473876953125,
-0.042236328125,
-0.048004150390625,
0.0041313... |
sadickam/sdg-classification-bert | 2023-07-01T11:47:27.000Z | [
"transformers",
"pytorch",
"safetensors",
"bert",
"text-classification",
"en",
"license:mit",
"endpoints_compatible",
"has_space",
"region:us"
] | text-classification | sadickam | null | null | sadickam/sdg-classification-bert | 4 | 11,062 | transformers | 2023-01-15T23:34:42 | ---
license: mit
language:
- en
metrics:
- accuracy
- matthews_correlation
---
# sadickam/sdg-classification-bert
<!-- Provide a quick summary of what the model is/does. -->
This model is for classifying text with respect to the United Nations sustainable development goals (SDG).
![image](https://user-images.github... | 3,123 | [
[
-0.035797119140625,
-0.031890869140625,
0.0193023681640625,
0.002552032470703125,
-0.032379150390625,
-0.0189666748046875,
-0.01300811767578125,
-0.04071044921875,
0.0032901763916015625,
0.03997802734375,
-0.0537109375,
-0.058837890625,
-0.06109619140625,
0.... |
openchat/openchat_v3.1 | 2023-09-24T10:11:15.000Z | [
"transformers",
"pytorch",
"llama",
"text-generation",
"arxiv:2309.11235",
"license:llama2",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | openchat | null | null | openchat/openchat_v3.1 | 5 | 11,055 | transformers | 2023-07-30T10:11:46 | ---
license: llama2
---
# OpenChat: Advancing Open-source Language Models with Imperfect Data</h1>
<div align="center">
<img src="https://raw.githubusercontent.com/imoneoi/openchat/master/assets/logo_new.png" style="width: 65%">
</div>
[OpenChat](https://github.com/imoneoi/openchat) is a series of open-source lang... | 8,932 | [
[
-0.0472412109375,
-0.06597900390625,
0.02362060546875,
0.03277587890625,
-0.01543426513671875,
-0.01110076904296875,
-0.021148681640625,
-0.03961181640625,
0.0239715576171875,
0.02764892578125,
-0.043701171875,
-0.03289794921875,
-0.033538818359375,
-0.02001... |
nitrosocke/Future-Diffusion | 2023-03-09T07:23:11.000Z | [
"diffusers",
"stable-diffusion",
"text-to-image",
"en",
"license:openrail++",
"has_space",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | nitrosocke | null | null | nitrosocke/Future-Diffusion | 397 | 11,043 | diffusers | 2022-11-24T23:43:44 | ---
license: openrail++
language:
- en
tags:
- stable-diffusion
- text-to-image
- diffusers
thumbnail: "https://huggingface.co/nitrosocke/Future-Diffusion/resolve/main/images/future-diffusion-thumbnail-2.jpg"
inference: false
---
### Future Diffusion
This is the fine-tuned Stable Diffusion 2.0 model trained on high q... | 2,268 | [
[
-0.035888671875,
-0.06365966796875,
0.04913330078125,
0.0146636962890625,
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0.01849365234375,
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0.0289154052734375,
0.0465087890625,
-0.052215576171875,
-0.03631591796875,
-0.053009033203125,
-0.02... |
uukuguy/speechless-codellama-platypus-13b | 2023-09-13T00:00:14.000Z | [
"transformers",
"pytorch",
"llama",
"text-generation",
"llama-2",
"en",
"dataset:garage-bAInd/Open-Platypus",
"arxiv:2308.12950",
"license:llama2",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | uukuguy | null | null | uukuguy/speechless-codellama-platypus-13b | 0 | 11,026 | transformers | 2023-08-31T12:32:35 | ---
language:
- en
library_name: transformers
pipeline_tag: text-generation
datasets:
- garage-bAInd/Open-Platypus
tags:
- llama-2
license: llama2
---
<p><h1> The Tool LLM Based on CodeLlama </h1></p>
Fine-tune the codellama/CodeLlama-13b-hf with Open-Platypus dataset.
| Metric | Value |
| --- | --- |
| ARC | 45.31 ... | 7,096 | [
[
-0.0283203125,
-0.05126953125,
0.0204010009765625,
0.03900146484375,
-0.01788330078125,
0.00765228271484375,
-0.01104736328125,
-0.04229736328125,
0.0203704833984375,
0.03338623046875,
-0.0299835205078125,
-0.047698974609375,
-0.041961669921875,
0.0190887451... |
uukuguy/speechless-codellama-orca-13b | 2023-09-12T23:57:47.000Z | [
"transformers",
"pytorch",
"llama",
"text-generation",
"llama-2",
"en",
"dataset:garage-bAInd/Open-Platypus",
"arxiv:2308.12950",
"license:llama2",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | uukuguy | null | null | uukuguy/speechless-codellama-orca-13b | 2 | 11,017 | transformers | 2023-09-04T03:07:26 | ---
language:
- en
library_name: transformers
pipeline_tag: text-generation
datasets:
- garage-bAInd/Open-Platypus
tags:
- llama-2
license: llama2
---
<p><h1> speechless-codellama-orca-13b </h1></p>
Fine-tune the codellama/CodeLlama-13b-hf with Orca dataset.
10k samples (7.56%)
| Metric | Value |
| --- | --- |
| ARC... | 7,104 | [
[
-0.0277862548828125,
-0.051605224609375,
0.0186920166015625,
0.039276123046875,
-0.016754150390625,
0.007293701171875,
-0.0088348388671875,
-0.04632568359375,
0.021697998046875,
0.03271484375,
-0.0310516357421875,
-0.0469970703125,
-0.042755126953125,
0.0205... |
digiplay/Juggernaut_final | 2023-07-10T23:21:23.000Z | [
"diffusers",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"license:other",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | digiplay | null | null | digiplay/Juggernaut_final | 8 | 11,014 | diffusers | 2023-07-10T22:56:03 | ---
license: other
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
inference: true
---
Models info :
https://civitai.com/models/46422?modelVersionId=114770
Sample image I made thru huggingface's API:
![1396153a-5288-40f0-a52a-1e3b8cd9ad29.jpeg](https://cdn-uploads.huggingface.co/pro... | 928 | [
[
-0.0477294921875,
-0.0416259765625,
0.0293426513671875,
0.0262908935546875,
-0.0245819091796875,
-0.003803253173828125,
0.0293731689453125,
-0.030517578125,
0.05377197265625,
0.03082275390625,
-0.0748291015625,
-0.040374755859375,
-0.0357666015625,
-0.001924... |
csebuetnlp/mT5_multilingual_XLSum | 2022-08-13T13:15:36.000Z | [
"transformers",
"pytorch",
"mt5",
"text2text-generation",
"summarization",
"mT5",
"am",
"ar",
"az",
"bn",
"my",
"zh",
"en",
"fr",
"gu",
"ha",
"hi",
"ig",
"id",
"ja",
"rn",
"ko",
"ky",
"mr",
"ne",
"om",
"ps",
"fa",
"pcm",
"pt",
"pa",
"ru",
"gd",
"sr",... | summarization | csebuetnlp | null | null | csebuetnlp/mT5_multilingual_XLSum | 185 | 10,995 | transformers | 2022-03-02T23:29:05 | ---
tags:
- summarization
- mT5
datasets:
- csebuetnlp/xlsum
language:
- am
- ar
- az
- bn
- my
- zh
- en
- fr
- gu
- ha
- hi
- ig
- id
- ja
- rn
- ko
- ky
- mr
- ne
- om
- ps
- fa
- pcm
- pt
- pa
- ru
- gd
- sr
- si
- so
- es
- sw
- ta
- te
- th
- ti
- tr
- uk
- ur
- uz
- vi
- cy
- yo
licenses:
- cc-by-nc-sa-4.0
widge... | 7,364 | [
[
-0.0306854248046875,
-0.0325927734375,
0.011383056640625,
0.0245361328125,
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0.0097503662109375,
-0.006866455078125,
-0.0274505615234375,
0.0272979736328125,
0.0100860595703125,
-0.02386474609375,
-0.044219970703125,
-0.057647705078125,
0... |
wenge-research/yayi-7b-llama2 | 2023-09-13T02:25:50.000Z | [
"transformers",
"pytorch",
"llama",
"text-generation",
"yayi",
"zh",
"en",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | wenge-research | null | null | wenge-research/yayi-7b-llama2 | 8 | 10,978 | transformers | 2023-07-21T10:10:18 | ---
language:
- zh
- en
pipeline_tag: text-generation
tags:
- yayi
---
# 雅意大模型
## 介绍
[雅意大模型](https://www.wenge.com/yayi/index.html)在百万级人工构造的高质量领域数据上进行指令微调得到，训练数据覆盖媒体宣传、舆情分析、公共安全、金融风控、城市治理等五大领域，上百种自然语言指令任务。雅意大模型从预训练初始化权重到领域模型的迭代过程中，我们逐步增强了它的中文基础能力和领域分析能力，并增加了多轮对话和部分插件能力。同时，经过数百名用户内测过程中持续不断的人工反馈优化，我们进一步提升了模型性能和安全性。
通过... | 7,684 | [
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-0.039825439453125,
0.01043701171875,
0.018096923828125,
-0.045257568359375,
-0.04290771484375,
-0.0418701171875,
0.0007300376... |
CalderaAI/30B-Epsilon | 2023-07-20T06:59:50.000Z | [
"transformers",
"pytorch",
"llama",
"text-generation",
"alpaca",
"vicuna",
"uncensored",
"cot",
"chain of thought",
"story",
"adventure",
"roleplay",
"rp",
"merge",
"mix",
"instruct",
"wizardlm",
"superhot",
"supercot",
"manticore",
"hippogriff",
"endpoints_compatible",
"... | text-generation | CalderaAI | null | null | CalderaAI/30B-Epsilon | 9 | 10,967 | transformers | 2023-07-07T08:12:03 | ---
tags:
- llama
- alpaca
- vicuna
- uncensored
- cot
- chain of thought
- story
- adventure
- roleplay
- rp
- merge
- mix
- instruct
- wizardlm
- superhot
- supercot
- manticore
- hippogriff
---
## 30B-Epsilon
Epsilon is an instruct based general purpose model assembled from hand picked models and LoRAs.
There is n... | 3,155 | [
[
-0.04730224609375,
-0.07073974609375,
0.0202484130859375,
0.031585693359375,
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0.05206298828125,
-0.057098388671875,
-0.036407470703125,
-0.0307769775390625,
-0.... |
wenge-research/yayi-13b-llama2 | 2023-09-13T02:24:34.000Z | [
"transformers",
"pytorch",
"llama",
"text-generation",
"yayi",
"zh",
"en",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | wenge-research | null | null | wenge-research/yayi-13b-llama2 | 6 | 10,952 | transformers | 2023-07-21T10:10:40 | ---
language:
- zh
- en
pipeline_tag: text-generation
tags:
- yayi
---
# 雅意大模型
## 介绍
[雅意大模型](https://www.wenge.com/yayi/index.html)在百万级人工构造的高质量领域数据上进行指令微调得到，训练数据覆盖媒体宣传、舆情分析、公共安全、金融风控、城市治理等五大领域，上百种自然语言指令任务。雅意大模型从预训练初始化权重到领域模型的迭代过程中，我们逐步增强了它的中文基础能力和领域分析能力，并增加了多轮对话和部分插件能力。同时，经过数百名用户内测过程中持续不断的人工反馈优化，我们进一步提升了模型性能和安全性。
通过... | 7,684 | [
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0.01806640625,
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-0.04290771484375,
-0.041900634765625,
0.0007357597... |
s-nlp/roberta_toxicity_classifier | 2021-10-05T14:54:55.000Z | [
"transformers",
"pytorch",
"roberta",
"text-classification",
"toxic comments classification",
"en",
"arxiv:1907.11692",
"endpoints_compatible",
"has_space",
"region:us"
] | text-classification | s-nlp | null | null | s-nlp/roberta_toxicity_classifier | 28 | 10,946 | transformers | 2022-03-02T23:29:05 | ---
language:
- en
tags:
- toxic comments classification
licenses:
- cc-by-nc-sa
---
## Toxicity Classification Model
This model is trained for toxicity classification task. The dataset used for training is the merge of the English parts of the three datasets by **Jigsaw** ([Jigsaw 2018](https://www.kaggle.com/c/jigs... | 1,653 | [
[
0.005859375,
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0.006015777587890625,
-0.0193023681640625,
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0.02972412109375,
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-0.05560302734375,
-0.05828857421875,
0.012252... |
TheBloke/Wizard-Vicuna-7B-Uncensored-GPTQ | 2023-09-27T12:44:19.000Z | [
"transformers",
"safetensors",
"llama",
"text-generation",
"uncensored",
"en",
"dataset:ehartford/wizard_vicuna_70k_unfiltered",
"license:other",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | TheBloke | null | null | TheBloke/Wizard-Vicuna-7B-Uncensored-GPTQ | 111 | 10,946 | transformers | 2023-05-18T07:53:47 | ---
language:
- en
license: other
tags:
- uncensored
datasets:
- ehartford/wizard_vicuna_70k_unfiltered
model_name: Wizard Vicuna 7B Uncensored
base_model: ehartford/Wizard-Vicuna-7B-Uncensored
inference: false
model_creator: Eric Hartford
model_type: llama
prompt_template: 'A chat between a curious user and an artific... | 16,834 | [
[
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0.032867431640625,
-0.041656494140625,
-0.03729248046875,
-0.027496337890625,
... |
Yntec/Luma | 2023-07-24T23:57:10.000Z | [
"diffusers",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"sadxzero",
"license:creativeml-openrail-m",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | Yntec | null | null | Yntec/Luma | 2 | 10,912 | diffusers | 2023-07-24T21:27:52 | ---
license: creativeml-openrail-m
library_name: diffusers
pipeline_tag: text-to-image
tags:
- stable-diffusion
- stable-diffusion-diffusers
- diffusers
- text-to-image
- sadxzero
---
# SXZ Luma 0.98 VAE
fp16noema version. Original pages:
https://civitai.com/models/25831?modelVersionId=68200 | 295 | [
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-0.066162109375,
-0.0178985595703125,
-0.00467681884765625... |
jjzha/jobbert_skill_extraction | 2023-10-26T10:25:11.000Z | [
"transformers",
"pytorch",
"safetensors",
"bert",
"token-classification",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | token-classification | jjzha | null | null | jjzha/jobbert_skill_extraction | 4 | 10,910 | transformers | 2023-04-06T13:41:51 | This is a demo using the models from:
```
@inproceedings{zhang-etal-2022-skillspan,
title = "{S}kill{S}pan: Hard and Soft Skill Extraction from {E}nglish Job Postings",
author = "Zhang, Mike and
Jensen, Kristian and
Sonniks, Sif and
Plank, Barbara",
booktitle = "Proceedings of the 2022... | 1,947 | [
[
-0.0179595947265625,
-0.05413818359375,
0.0180206298828125,
0.0198211669921875,
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-0.03436279296875,
-0.0416259765625,
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0.044647216796875,
-0.04547119140625,
-0.03460693359375,
-0.042999267578125,
... |
Xwin-LM/Xwin-LM-70B-V0.1 | 2023-09-21T09:55:27.000Z | [
"transformers",
"pytorch",
"llama",
"text-generation",
"license:llama2",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | Xwin-LM | null | null | Xwin-LM/Xwin-LM-70B-V0.1 | 171 | 10,870 | transformers | 2023-09-15T14:04:14 | ---
license: llama2
---
<h3 align="center">
Xwin-LM: Powerful, Stable, and Reproducible LLM Alignment
</h3>
<p align="center">
<a href="https://github.com/Xwin-LM/Xwin-LM">
<img src="https://img.shields.io/badge/GitHub-yellow.svg?style=social&logo=github">
</a>
<a href="https://huggingface.co/Xwin-LM">
... | 9,826 | [
[
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-0.053497314453125,
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... |
Helsinki-NLP/opus-mt-hu-en | 2023-08-16T11:57:55.000Z | [
"transformers",
"pytorch",
"tf",
"marian",
"text2text-generation",
"translation",
"hu",
"en",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | translation | Helsinki-NLP | null | null | Helsinki-NLP/opus-mt-hu-en | 1 | 10,837 | transformers | 2022-03-02T23:29:04 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-hu-en
* source languages: hu
* target languages: en
* OPUS readme: [hu-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/hu-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... | 818 | [
[
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0.027374267578125,
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-0.031341552734375,
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0.036285400390625,
-0.045501708984375,
-0.042816162109375,
-0.03729248046875,
0.... |
JosefJilek/loliDiffusion | 2023-10-17T19:29:57.000Z | [
"diffusers",
"art",
"anime",
"text-to-image",
"license:creativeml-openrail-m",
"has_space",
"region:us"
] | text-to-image | JosefJilek | null | null | JosefJilek/loliDiffusion | 177 | 10,833 | diffusers | 2023-02-28T21:14:14 | ---
license: creativeml-openrail-m
pipeline_tag: text-to-image
tags:
- art
- anime
library_name: diffusers
---
# Loli Diffusion
The goal of this project is to improve generation of loli characters since most of other models are not good at it. \
__Support me: https://www.buymeacoffee.com/jilek772003__
## Usage
It is... | 4,012 | [
[
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0.048492431640625,
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0.0094... |
cross-encoder/quora-distilroberta-base | 2021-08-05T08:41:31.000Z | [
"transformers",
"pytorch",
"jax",
"roberta",
"text-classification",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-classification | cross-encoder | null | null | cross-encoder/quora-distilroberta-base | 1 | 10,828 | transformers | 2022-03-02T23:29:05 | ---
license: apache-2.0
---
# Cross-Encoder for Quora Duplicate Questions Detection
This model was trained using [SentenceTransformers](https://sbert.net) [Cross-Encoder](https://www.sbert.net/examples/applications/cross-encoder/README.html) class.
## Training Data
This model was trained on the [Quora Duplicate Questi... | 1,070 | [
[
-0.0268707275390625,
-0.06695556640625,
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0.0099639892578125,
-0.0208282470703125,
-0.0066986083984375,
0.0138092041015625,
-0.0160064697265625,
0.0097198486328125,
0.0472412109375,
-0.04754638671875,
-0.024658203125,
-0.038421630859375,
0... |
daveni/twitter-xlm-roberta-emotion-es | 2022-04-28T09:49:06.000Z | [
"transformers",
"pytorch",
"xlm-roberta",
"text-classification",
"Emotion Analysis",
"es",
"endpoints_compatible",
"region:us"
] | text-classification | daveni | null | null | daveni/twitter-xlm-roberta-emotion-es | 13 | 10,824 | transformers | 2022-03-02T23:29:05 | ---
language:
- es
tags:
- Emotion Analysis
---
**Note**: This model & model card are based on the [finetuned XLM-T for Sentiment Analysis](https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base-sentiment)
# twitter-XLM-roBERTa-base for Emotion Analysis
This is a XLM-roBERTa-base model trained on ~198M tweets ... | 3,814 | [
[
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-0.05352783203125,
0.01132965087890625,
0.0247650146484375,
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0.004283905029296875,
-0.047607421875,
-0.06524658203125,
-0.058197021484375,
0.00... |
Maykeye/TinyLLama-v0 | 2023-07-26T05:04:57.000Z | [
"transformers",
"pytorch",
"safetensors",
"llama",
"text-generation",
"license:apache-2.0",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | Maykeye | null | null | Maykeye/TinyLLama-v0 | 7 | 10,815 | transformers | 2023-07-08T04:50:15 | ---
license: apache-2.0
---
This is a first version of recreating roneneldan/TinyStories-1M but using Llama architecture.
* Full training process is included in the notebook train.ipynb. Recreating it as simple as downloading
TinyStoriesV2-GPT4-train.txt and TinyStoriesV2-GPT4-valid.txt in the same folder with the no... | 1,641 | [
[
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-0.00508880615234375,
-0.0267486572265625,
0.023223876953125,
0.029296875,
-0.05999755859375,
-0.00984954833984375,
-0.0253143310546875,
0... |
timm/vit_large_patch16_224.augreg_in21k_ft_in1k | 2023-05-06T00:18:01.000Z | [
"timm",
"pytorch",
"safetensors",
"image-classification",
"dataset:imagenet-1k",
"dataset:imagenet-21k",
"arxiv:2106.10270",
"arxiv:2010.11929",
"license:apache-2.0",
"region:us"
] | image-classification | timm | null | null | timm/vit_large_patch16_224.augreg_in21k_ft_in1k | 1 | 10,806 | timm | 2022-12-22T07:46:31 | ---
tags:
- image-classification
- timm
library_name: timm
license: apache-2.0
datasets:
- imagenet-1k
- imagenet-21k
---
# Model card for vit_large_patch16_224.augreg_in21k_ft_in1k
A Vision Transformer (ViT) image classification model. Trained on ImageNet-21k and fine-tuned on ImageNet-1k (with additional augmentatio... | 3,911 | [
[
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-0.0297088623046875,
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-0.0232696533203125,
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0.01556396484375,
0.02392578125,
-0.040496826171875,
-0.0374755859375,
-0.048095703125,
0.000... |
allenai/scibert_scivocab_cased | 2022-10-03T22:04:46.000Z | [
"transformers",
"pytorch",
"jax",
"bert",
"en",
"endpoints_compatible",
"has_space",
"region:us"
] | null | allenai | null | null | allenai/scibert_scivocab_cased | 8 | 10,785 | transformers | 2022-03-02T23:29:05 | ---
language: en
---
# SciBERT
This is the pretrained model presented in [SciBERT: A Pretrained Language Model for Scientific Text](https://www.aclweb.org/anthology/D19-1371/), which is a BERT model trained on scientific text.
The training corpus was papers taken from [Semantic Scholar](https://www.semanticscholar.or... | 1,135 | [
[
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0.028778076171875,
0.023468017578125,
-0.02960205078125,
-0.0416259765625,
-0.042694091796875,
0.0141... |
bigcode/tiny_starcoder_py | 2023-06-01T15:14:56.000Z | [
"transformers",
"pytorch",
"safetensors",
"gpt_bigcode",
"text-generation",
"code",
"dataset:bigcode/the-stack-dedup",
"license:bigcode-openrail-m",
"model-index",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | bigcode | null | null | bigcode/tiny_starcoder_py | 58 | 10,783 | transformers | 2023-05-15T07:43:22 | ---
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: Tiny-StarCoder-Py
results:
- tas... | 2,703 | [
[
-0.035675048828125,
-0.03973388671875,
0.0318603515625,
0.0064849853515625,
-0.02154541015625,
-0.0258636474609375,
-0.0176849365234375,
-0.014984130859375,
-0.0056610107421875,
0.025360107421875,
-0.0457763671875,
-0.0194091796875,
-0.051361083984375,
-0.00... |
Helsinki-NLP/opus-tatoeba-en-ja | 2023-09-19T11:15:18.000Z | [
"transformers",
"pytorch",
"tf",
"marian",
"text2text-generation",
"translation",
"en",
"ja",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | translation | Helsinki-NLP | null | null | Helsinki-NLP/opus-tatoeba-en-ja | 7 | 10,757 | transformers | 2022-03-02T23:29:04 | ---
language:
- en
- ja
tags:
- translation
license: apache-2.0
---
### en-ja
* source group: English
* target group: Japanese
* OPUS readme: [eng-jpn](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-jpn/README.md)
* model: transformer-align
* source language(s): eng
* target language(s... | 2,176 | [
[
-0.0251922607421875,
-0.05078125,
0.024078369140625,
0.03192138671875,
-0.040130615234375,
-0.01505279541015625,
-0.0305633544921875,
-0.0273895263671875,
0.024444580078125,
0.0242919921875,
-0.049957275390625,
-0.05792236328125,
-0.04473876953125,
0.0343017... |
tals/albert-base-vitaminc-mnli | 2022-08-05T02:27:22.000Z | [
"transformers",
"pytorch",
"albert",
"text-classification",
"dataset:glue",
"dataset:multi_nli",
"dataset:tals/vitaminc",
"endpoints_compatible",
"region:us"
] | text-classification | tals | null | null | tals/albert-base-vitaminc-mnli | 0 | 10,751 | transformers | 2022-03-02T23:29:05 | ---
datasets:
- glue
- multi_nli
- tals/vitaminc
---
# Details
Model used in [Get Your Vitamin C! Robust Fact Verification with Contrastive Evidence](https://aclanthology.org/2021.naacl-main.52/) (Schuster et al., NAACL 21`).
For more details see: https://github.com/TalSchuster/VitaminC
When using this model, please ... | 2,344 | [
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0.01326751708984375,
-0.0159759521484375,
-0.05255126953125,
0.014251708984375,
0.00348663330078125,
-0.026824951171875,
-0.045379638671875,
-0.0365295410156... |
valentinafeve/yolos-fashionpedia | 2023-03-10T13:11:26.000Z | [
"transformers",
"pytorch",
"yolos",
"object-detection",
"YOLOS",
"Object detection",
"en",
"dataset:detection-datasets/fashionpedia",
"endpoints_compatible",
"has_space",
"region:us"
] | object-detection | valentinafeve | null | null | valentinafeve/yolos-fashionpedia | 41 | 10,744 | transformers | 2022-11-17T16:04:03 | ---
datasets:
- detection-datasets/fashionpedia
language:
- en
pipeline_tag: object-detection
tags:
- YOLOS
- Object detection
---
This is a fine-tunned object detection model for fashion.
For more details of the implementation you can check the source code [here](https://github.com/valntinaf/fine_tunning_YOLOS_for_f... | 1,120 | [
[
-0.043609619140625,
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0.01025390625,
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0.01837158203125,
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0.020721435546875,
0.03216552734375,
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-0.06365966796875,
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0.006... |
timm/resnet34d.ra2_in1k | 2023-04-05T18:07:44.000Z | [
"timm",
"pytorch",
"safetensors",
"image-classification",
"arxiv:2110.00476",
"arxiv:1512.03385",
"arxiv:1812.01187",
"license:apache-2.0",
"region:us"
] | image-classification | timm | null | null | timm/resnet34d.ra2_in1k | 0 | 10,728 | timm | 2023-04-05T18:07:30 | ---
tags:
- image-classification
- timm
library_tag: timm
license: apache-2.0
---
# Model card for resnet34d.ra2_in1k
A ResNet-D image classification model.
This model features:
* ReLU activations
* 3-layer stem of 3x3 convolutions with pooling
* 2x2 average pool + 1x1 convolution shortcut downsample
Trained on I... | 39,084 | [
[
-0.06353759765625,
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-0.040069580078125,
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timm/tf_efficientnet_lite2.in1k | 2023-04-27T21:38:22.000Z | [
"timm",
"pytorch",
"safetensors",
"image-classification",
"dataset:imagenet-1k",
"arxiv:1905.11946",
"license:apache-2.0",
"region:us"
] | image-classification | timm | null | null | timm/tf_efficientnet_lite2.in1k | 0 | 10,724 | timm | 2022-12-13T00:13:43 | ---
tags:
- image-classification
- timm
library_name: timm
license: apache-2.0
datasets:
- imagenet-1k
---
# Model card for tf_efficientnet_lite2.in1k
A EfficientNet-Lite image classification model. Trained on ImageNet-1k in Tensorflow by paper authors, ported to PyTorch by Ross Wightman.
## Model Details
- **Model ... | 4,088 | [
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-0.045623779296875,
-0.0539550781... |
princeton-nlp/Sheared-LLaMA-2.7B | 2023-11-01T14:51:37.000Z | [
"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-2.7B | 41 | 10,709 | transformers | 2023-10-10T15:37:39 | ---
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/pri... | 2,714 | [
[
-0.0225982666015625,
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0.0289306640625,
0.021728515625,
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-0.0400390625,
-0.0599365234375,
0.0090332... |
bigcode/santacoder | 2023-10-12T16:41:58.000Z | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"custom_code",
"code",
"dataset:bigcode/the-stack",
"arxiv:1911.02150",
"arxiv:2207.14255",
"arxiv:2301.03988",
"license:bigcode-openrail-m",
"model-index",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | bigcode | null | null | bigcode/santacoder | 303 | 10,700 | transformers | 2022-12-02T16:20:58 | ---
license: bigcode-openrail-m
datasets:
- bigcode/the-stack
language:
- code
programming_language:
- Java
- JavaScript
- Python
pipeline_tag: text-generation
inference: true
widget:
- text: 'def print_hello_world():'
example_title: Hello world
group: Python
model-index:
- name: SantaCoder
results:
- task:
... | 9,461 | [
[
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0.0049... |
Qwen/Qwen-14B-Chat-Int4 | 2023-11-05T03:27:21.000Z | [
"transformers",
"safetensors",
"qwen",
"text-generation",
"custom_code",
"zh",
"en",
"arxiv:2309.16609",
"arxiv:2305.08322",
"arxiv:2009.03300",
"arxiv:2305.05280",
"arxiv:2210.03629",
"has_space",
"region:us"
] | text-generation | Qwen | null | null | Qwen/Qwen-14B-Chat-Int4 | 82 | 10,698 | transformers | 2023-09-24T03:27:30 | ---
language:
- zh
- en
tags:
- qwen
pipeline_tag: text-generation
inference: false
---
# Qwen-14B-Chat-Int4
<p align="center">
<img src="https://qianwen-res.oss-cn-beijing.aliyuncs.com/logo_qwen.jpg" width="400"/>
<p>
<br>
<p align="center">
🤗 <a href="https://huggingface.co/Qwen">Hugging Face</a> ... | 26,699 | [
[
-0.0341796875,
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0.0072479248046875,
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-0.036376953125,
... |
OFA-Sys/chinese-clip-vit-base-patch16 | 2022-12-09T06:10:13.000Z | [
"transformers",
"pytorch",
"chinese_clip",
"zero-shot-image-classification",
"vision",
"arxiv:2211.01335",
"endpoints_compatible",
"has_space",
"region:us"
] | zero-shot-image-classification | OFA-Sys | null | null | OFA-Sys/chinese-clip-vit-base-patch16 | 37 | 10,697 | transformers | 2022-11-09T08:14:09 | ---
tags:
- vision
widget:
- src: https://huggingface.co/OFA-Sys/chinese-clip-vit-base-patch16/resolve/main/festival.jpg
candidate_labels: 灯笼, 鞭炮, 对联
example_title: festival
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/cat-dog-music.png
candidate_labels: 音乐表演, 体育运动
example_title: cat... | 7,628 | [
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0.03216552734375,
-0.0001367330551147461,
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-0.04101... |
facebook/timesformer-base-finetuned-k400 | 2023-01-02T11:43:07.000Z | [
"transformers",
"pytorch",
"timesformer",
"video-classification",
"vision",
"arxiv:2102.05095",
"license:cc-by-nc-4.0",
"endpoints_compatible",
"has_space",
"region:us"
] | video-classification | facebook | null | null | facebook/timesformer-base-finetuned-k400 | 18 | 10,688 | transformers | 2022-10-07T19:03:04 | ---
license: "cc-by-nc-4.0"
tags:
- vision
- video-classification
---
# TimeSformer (base-sized model, fine-tuned on Kinetics-400)
TimeSformer model pre-trained on [Kinetics-400](https://www.deepmind.com/open-source/kinetics). It was introduced in the paper [TimeSformer: Is Space-Time Attention All You Need for Vide... | 1,926 | [
[
-0.01873779296875,
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-0.0009164810180664062,
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-0.0020294189453125,
-0.00862884521484375,
-0.057891845703125,
-0.0270538330078125,
-0.061157226... |
Joeythemonster/anything-midjourney-v-4-1 | 2023-05-16T09:40:13.000Z | [
"diffusers",
"text-to-image",
"stable-diffusion",
"license:creativeml-openrail-m",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | Joeythemonster | null | null | Joeythemonster/anything-midjourney-v-4-1 | 163 | 10,655 | diffusers | 2022-12-24T21:28:53 | ---
license: creativeml-openrail-m
tags:
- text-to-image
- stable-diffusion
---
### ANYTHING-MIDJOURNEY-V-4.1 Dreambooth model trained by Joeythemonster with [TheLastBen's fast-DreamBooth](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast-DreamBooth.ipynb) notebook
Test the conc... | 715 | [
[
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0.034942626953125,
-0.020904541015625,
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0.0252227783203125,
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0.01508331298828125,
-0.04742431640625,
-0.0228729248046875,
-0.0245819091796875,
... |
Yntec/AnythingV3-768 | 2023-10-26T10:46:45.000Z | [
"diffusers",
"anime",
"general",
"Linaqruf",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"en",
"license:creativeml-openrail-m",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | Yntec | null | null | Yntec/AnythingV3-768 | 2 | 10,646 | diffusers | 2023-10-26T09:20:09 | ---
language:
- en
license: creativeml-openrail-m
tags:
- anime
- general
- Linaqruf
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
inference: true
---
# Anything V3
768x768 version of this model with the MoistMix V2 VAE baked in for the Inference API. Original page: https://huggingface.c... | 805 | [
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0.057342529296875,
-0.03253173828125,
-0.032470703125,
-0.038726806640625,
-0.0... |
MilaNLProc/feel-it-italian-emotion | 2022-08-15T20:36:13.000Z | [
"transformers",
"pytorch",
"tf",
"camembert",
"text-classification",
"sentiment",
"emotion",
"Italian",
"it",
"endpoints_compatible",
"has_space",
"region:us"
] | text-classification | MilaNLProc | null | null | MilaNLProc/feel-it-italian-emotion | 13 | 10,636 | transformers | 2022-03-02T23:29:04 | ---
language: it
tags:
- sentiment
- emotion
- Italian
---
# FEEL-IT: Emotion and Sentiment Classification for the Italian Language
## FEEL-IT Python Package
You can find the package that uses this model for emotion and sentiment classification **[here](https://github.com/MilaNLProc/feel-it)** it is meant to... | 3,607 | [
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0.015... |
Helsinki-NLP/opus-mt-en-ROMANCE | 2023-08-16T11:28:52.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"rust",
"marian",
"text2text-generation",
"translation",
"en",
"roa",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | translation | Helsinki-NLP | null | null | Helsinki-NLP/opus-mt-en-ROMANCE | 6 | 10,634 | transformers | 2022-03-02T23:29:04 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-en-ROMANCE
* source languages: en
* target 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... | 2,259 | [
[
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0.0162200927734375,
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0... |
ToddGoldfarb/Cadet-Tiny | 2023-05-12T00:18:41.000Z | [
"transformers",
"pytorch",
"t5",
"text2text-generation",
"conversational",
"en",
"dataset:allenai/soda",
"license:openrail",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | conversational | ToddGoldfarb | null | null | ToddGoldfarb/Cadet-Tiny | 5 | 10,631 | transformers | 2023-04-07T06:34:12 | ---
license: openrail
datasets:
- allenai/soda
language:
- en
pipeline_tag: conversational
---
# What is Cadet-Tiny?
Inspired by Allen AI's **Cosmo-XL**, **Cadet-Tiny** is a _very small_ conversational model trained off of the **SODA** dataset. **Cadet-Tiny** is intended for inference at the edge (on something as smal... | 5,737 | [
[
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0.0230865478515625,
0.007678985595703125,
-0.05157470703125,
-0.0308837890625,
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... |
facebook/rag-sequence-nq | 2021-03-12T11:04:28.000Z | [
"transformers",
"pytorch",
"tf",
"rag",
"en",
"dataset:wiki_dpr",
"arxiv:2005.11401",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | facebook | null | null | facebook/rag-sequence-nq | 15 | 10,627 | 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-Sequence 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, A... | 1,739 | [
[
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-0.0033245086669921875,
-0.00848388671875,
0.016082763671875,
0.035858154296875,
-0.037872314453125,
-0.0032196044921875,
-0.036773681640625,... |
dbmdz/bert-base-italian-uncased | 2021-05-19T15:00:42.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"it",
"dataset:wikipedia",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | fill-mask | dbmdz | null | null | dbmdz/bert-base-italian-uncased | 4 | 10,618 | transformers | 2022-03-02T23:29:05 | ---
language: it
license: mit
datasets:
- wikipedia
---
# 🤗 + 📚 dbmdz BERT and ELECTRA models
In this repository the MDZ Digital Library team (dbmdz) at the Bavarian State
Library open sources Italian BERT and ELECTRA models 🎉
# Italian BERT
The source data for the Italian BERT model consists of a recent Wikiped... | 5,994 | [
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... |
KB/bert-base-swedish-cased-ner | 2022-06-07T16:34:49.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"bert",
"token-classification",
"sv",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | token-classification | KB | null | null | KB/bert-base-swedish-cased-ner | 4 | 10,612 | transformers | 2022-06-07T16:31:50 | ---
language: sv
---
# Swedish BERT Models
The National Library of Sweden / KBLab releases three pretrained language models based on BERT and ALBERT. The models are trained on approximately 15-20GB of text (200M sentences, 3000M tokens) from various sources (books, news, government publications, swedish wikipedia and... | 6,166 | [
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-0.0374755859375,
-0.050018310546875,
-0.046051025390625,
0.01337432... |
keremberke/yolov8m-table-extraction | 2023-02-22T13:03:02.000Z | [
"ultralytics",
"tensorboard",
"v8",
"ultralyticsplus",
"yolov8",
"yolo",
"vision",
"object-detection",
"pytorch",
"awesome-yolov8-models",
"dataset:keremberke/table-extraction",
"model-index",
"has_space",
"region:us"
] | object-detection | keremberke | null | null | keremberke/yolov8m-table-extraction | 13 | 10,594 | ultralytics | 2023-01-29T04:54:05 |
---
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/yolov8m-table-extraction
results:
- task:
type:... | 1,796 | [
[
-0.03839111328125,
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-0.0037... |
PrimeQA/nq_tydi_sq1-reader-xlmr_large-20221110 | 2022-11-14T19:47:16.000Z | [
"transformers",
"pytorch",
"xlm-roberta",
"MRC",
"TyDiQA",
"Natural Questions",
"SQuAD",
"xlm-roberta-large",
"multilingual",
"arxiv:1606.05250",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | PrimeQA | null | null | PrimeQA/nq_tydi_sq1-reader-xlmr_large-20221110 | 1 | 10,548 | transformers | 2022-11-14T19:20:52 | ---
license: apache-2.0
tags:
- MRC
- TyDiQA
- Natural Questions
- SQuAD
- xlm-roberta-large
language:
- multilingual
---
*Task*: MRC
# Model description
An XLM-RoBERTa Large reading comprehension model trained from the combination of TyDi, NQ, and SQuAD v1 datasets, starting from a fine-tuned [Tydi xlm-roberta-large... | 2,864 | [
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-0.01506805419921875,
-0.0259857177734375,
-0.000024020671844482422,
0.03411865234375,
-0.06622314453125,
-0.04296875,
-0.024322509765625,
0.0... |
openmmlab/upernet-convnext-tiny | 2023-04-24T07:14:02.000Z | [
"transformers",
"pytorch",
"safetensors",
"upernet",
"vision",
"image-segmentation",
"en",
"arxiv:1807.10221",
"arxiv:2201.03545",
"license:mit",
"endpoints_compatible",
"has_space",
"region:us"
] | image-segmentation | openmmlab | null | null | openmmlab/upernet-convnext-tiny | 1 | 10,514 | transformers | 2023-01-13T14:23:12 | ---
language: en
license: mit
tags:
- vision
- image-segmentation
model_name: openmmlab/upernet-convnext-tiny
---
# UperNet, ConvNeXt tiny-sized backbone
UperNet framework for semantic segmentation, leveraging a ConvNeXt backbone. UperNet was introduced in the paper [Unified Perceptual Parsing for Scene Understanding... | 1,554 | [
[
-0.04302978515625,
-0.0177459716796875,
0.01873779296875,
0.0340576171875,
-0.0258331298828125,
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0.0165557861328125,
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0.05352783203125,
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-0.03753662109375,
-0.0245819091796875,
-0.015... |
liuhaotian/llava-llama-2-13b-chat-lightning-preview | 2023-07-31T04:11:25.000Z | [
"transformers",
"pytorch",
"llava",
"text-generation",
"region:us",
"has_space"
] | text-generation | liuhaotian | null | null | liuhaotian/llava-llama-2-13b-chat-lightning-preview | 39 | 10,514 | transformers | 2023-07-19T07:38:47 | ---
inference: false
---
<br>
<br>
# LLaVA Model Card
## Model details
**Model type:**
LLaVA is an open-source chatbot trained by fine-tuning LLaMA/Vicuna on GPT-generated multimodal instruction-following data.
It is an auto-regressive language model, based on the transformer architecture.
**Model date:**
LLaVA-LL... | 1,660 | [
[
-0.004566192626953125,
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-0.037109375,
-0.04119873046875,
-0.0399169921875,
-0.00379... |
togethercomputer/RedPajama-INCITE-Base-3B-v1 | 2023-05-09T14:59:20.000Z | [
"transformers",
"pytorch",
"gpt_neox",
"text-generation",
"en",
"dataset:togethercomputer/RedPajama-Data-1T",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | togethercomputer | null | null | togethercomputer/RedPajama-INCITE-Base-3B-v1 | 82 | 10,471 | transformers | 2023-05-04T05:51:02 | ---
license: apache-2.0
language:
- en
datasets:
- togethercomputer/RedPajama-Data-1T
---
# RedPajama-INCITE-Base-3B-v1
RedPajama-INCITE-Base-3B-v1 was developed by Together and leaders from the open-source AI community including Ontocord.ai, ETH DS3Lab, AAI CERC, Université de Montréal, MILA - Québec AI Institute, S... | 8,571 | [
[
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0.028045654296875,
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lassl/roberta-ko-small | 2022-02-19T09:49:04.000Z | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"korean",
"lassl",
"ko",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | fill-mask | lassl | null | null | lassl/roberta-ko-small | 2 | 10,465 | transformers | 2022-03-02T23:29:05 | ---
license: apache-2.0
language: ko
tags:
- korean
- lassl
mask_token: "<mask>"
widget:
- text: 대한민국의 수도는 <mask> 입니다.
---
# LASSL roberta-ko-small
## How to use
```python
from transformers import AutoModel, AutoTokenizer
model = AutoModel.from_pretrained("lassl/roberta-ko-small")
tokenizer = AutoTokenizer.from... | 1,221 | [
[
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0.006717681884765625,
0.0229034423828125,
-0.04461669921875,
-0.044036865234375,
-0.055389404296875,
... |
nitrosocke/Arcane-Diffusion | 2023-05-16T09:20:36.000Z | [
"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/Arcane-Diffusion | 743 | 10,442 | diffusers | 2022-10-02T11:41:27 | ---
license: creativeml-openrail-m
tags:
- stable-diffusion
- text-to-image
---
# Arcane Diffusion
This is the fine-tuned Stable Diffusion model trained on images from the TV Show Arcane.
Use the tokens **_arcane style_** in your prompts for the effect.
**If you enjoy my work, please consider supporting me**
[![Becom... | 3,398 | [
[
-0.040191650390625,
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0.00634765625,
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0.0002963542938232422,
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0.033233642578125,
0.046539306640625,
-0.0244598388671875,
-0.04376220703125,
-0.046661376953125,
-... |
Salesforce/instructblip-vicuna-13b | 2023-07-17T12:36:49.000Z | [
"transformers",
"pytorch",
"instructblip",
"text2text-generation",
"vision",
"image-captioning",
"image-to-text",
"en",
"arxiv:2305.06500",
"license:other",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | image-to-text | Salesforce | null | null | Salesforce/instructblip-vicuna-13b | 33 | 10,442 | transformers | 2023-06-03T14:46:46 | ---
language: en
license: other
tags:
- vision
- image-captioning
pipeline_tag: image-to-text
---
# InstructBLIP model
InstructBLIP model using [Vicuna-13b](https://github.com/lm-sys/FastChat#model-weights) as language model. InstructBLIP was introduced in the paper [InstructBLIP: Towards General-purpose Vision-Langu... | 2,143 | [
[
-0.035125732421875,
-0.0521240234375,
0.003742218017578125,
0.031524658203125,
-0.0238494873046875,
-0.0062713623046875,
-0.00652313232421875,
-0.04876708984375,
-0.0013608932495117188,
0.036773681640625,
-0.05181884765625,
-0.029541015625,
-0.04034423828125,
... |
facebook/hubert-large-ll60k | 2021-11-05T12:42:57.000Z | [
"transformers",
"pytorch",
"tf",
"hubert",
"feature-extraction",
"speech",
"en",
"dataset:libri-light",
"arxiv:2106.07447",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | feature-extraction | facebook | null | null | facebook/hubert-large-ll60k | 16 | 10,436 | transformers | 2022-03-02T23:29:05 | ---
language: en
datasets:
- libri-light
tags:
- speech
license: apache-2.0
---
# Hubert-Large
[Facebook's Hubert](https://ai.facebook.com/blog/hubert-self-supervised-representation-learning-for-speech-recognition-generation-and-compression)
The large model pretrained on 16kHz sampled speech audio. When using the m... | 2,687 | [
[
-0.0264434814453125,
-0.035400390625,
0.0291900634765625,
0.01275634765625,
-0.0157928466796875,
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-0.0293731689453125,
-0.037933349609375,
0.014801025390625,
0.0208740234375,
-0.04718017578125,
-0.0280609130859375,
-0.03167724609375,
-0.01... |
kandinsky-community/kandinsky-2-1 | 2023-10-09T11:33:20.000Z | [
"diffusers",
"text-to-image",
"kandinsky",
"license:apache-2.0",
"has_space",
"diffusers:KandinskyPipeline",
"region:us"
] | text-to-image | kandinsky-community | null | null | kandinsky-community/kandinsky-2-1 | 28 | 10,422 | diffusers | 2023-05-24T09:52:07 | ---
license: apache-2.0
prior:
- kandinsky-community/kandinsky-2-1-prior
tags:
- text-to-image
- kandinsky
inference: false
---
# Kandinsky 2.1
Kandinsky 2.1 inherits best practices from Dall-E 2 and Latent diffusion while introducing some new ideas.
It uses the CLIP model as a text and image encoder, and diffusio... | 6,929 | [
[
-0.0301971435546875,
-0.054595947265625,
0.036773681640625,
0.014801025390625,
-0.0226898193359375,
-0.006977081298828125,
-0.0028228759765625,
-0.0206146240234375,
0.0019140243530273438,
0.029327392578125,
-0.0282135009765625,
-0.038604736328125,
-0.04083251953... |
facebook/deit-base-distilled-patch16-384 | 2023-09-12T20:40:32.000Z | [
"transformers",
"pytorch",
"tf",
"safetensors",
"deit",
"image-classification",
"vision",
"dataset:imagenet",
"arxiv:2012.12877",
"arxiv:2006.03677",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | image-classification | facebook | null | null | facebook/deit-base-distilled-patch16-384 | 4 | 10,401 | transformers | 2022-03-02T23:29:05 | ---
license: apache-2.0
tags:
- image-classification
- vision
datasets:
- imagenet
---
# Distilled Data-efficient Image Transformer (base-sized model)
Distilled data-efficient Image Transformer (DeiT) model pre-trained at resolution 224x224 and fine-tuned at resolution 384x384 on ImageNet-1k (1 million images, 1,000 ... | 6,869 | [
[
-0.058746337890625,
-0.038116455078125,
0.004673004150390625,
0.00991058349609375,
-0.03021240234375,
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-0.01226806640625,
-0.033843994140625,
0.0211334228515625,
0.0136566162109375,
-0.0302734375,
-0.0272216796875,
-0.0662841796875,
0.006... |
Yntec/BeautyFool | 2023-10-18T23:56:47.000Z | [
"diffusers",
"General",
"Base Model",
"53rt5355iz",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"license:other",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | Yntec | null | null | Yntec/BeautyFool | 1 | 10,398 | diffusers | 2023-10-18T22:25:16 | ---
license: other
tags:
- General
- Base Model
- 53rt5355iz
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
inference: true
---
# BeautyFool 1.2
This model with the MoistMixV2 VAE baked in.
Comparison:
![image/png](https://cdn-uploads.huggingface.co/production/uploads/63239b8370edc53f51... | 913 | [
[
-0.00589752197265625,
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0.033843994140625,
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0.040557861328125,
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0.0521240234375,
0.05706787109375,
-0.046142578125,
-0.025421142578125,
-0.0301055908203125,
... |
microsoft/deberta-v3-xsmall | 2022-09-26T08:59:28.000Z | [
"transformers",
"pytorch",
"tf",
"deberta-v2",
"deberta",
"deberta-v3",
"fill-mask",
"en",
"arxiv:2006.03654",
"arxiv:2111.09543",
"license:mit",
"endpoints_compatible",
"region:us"
] | fill-mask | microsoft | null | null | microsoft/deberta-v3-xsmall | 27 | 10,397 | transformers | 2022-03-02T23:29:05 | ---
language: en
tags:
- deberta
- deberta-v3
- fill-mask
thumbnail: https://huggingface.co/front/thumbnails/microsoft.png
license: mit
---
## DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing
[DeBERTa](https://arxiv.org/abs/2006.03654) improves the BERT... | 3,727 | [
[
-0.031494140625,
-0.043701171875,
0.0206146240234375,
0.0222625732421875,
-0.0164642333984375,
0.0097198486328125,
-0.005756378173828125,
-0.031707763671875,
0.0250396728515625,
0.002788543701171875,
-0.028594970703125,
-0.039215087890625,
-0.0662841796875,
... |
bmd1905/vietnamese-correction | 2023-03-21T15:33:18.000Z | [
"transformers",
"pytorch",
"safetensors",
"mbart",
"text2text-generation",
"generated_from_trainer",
"vi",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text2text-generation | bmd1905 | null | null | bmd1905/vietnamese-correction | 2 | 10,397 | transformers | 2023-02-26T07:34:05 | ---
tags:
- generated_from_trainer
model-index:
- name: bartpho-syllable-finetuned-vietnamese_correction
results: []
license: apache-2.0
language:
- vi
---
# bartpho-syllable-finetuned-vietnamese_correction
This model is a fine-tuned version of [vinai/bartpho-syllable](https://github.com/VinAIResearch/BARTpho). The... | 1,993 | [
[
0.004730224609375,
-0.0523681640625,
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0.05255126953125,
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-0.032440185546875,
0.04... |
microsoft/Multilingual-MiniLM-L12-H384 | 2022-08-10T07:27:42.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"bert",
"text-classification",
"multilingual",
"en",
"ar",
"bg",
"de",
"el",
"es",
"fr",
"hi",
"ru",
"sw",
"th",
"tr",
"ur",
"vi",
"zh",
"arxiv:2002.10957",
"arxiv:1809.05053",
"arxiv:1911.02116",
"arxiv:1910.07475",
"licens... | text-classification | microsoft | null | null | microsoft/Multilingual-MiniLM-L12-H384 | 46 | 10,383 | transformers | 2022-03-02T23:29:05 | ---
language:
- multilingual
- en
- ar
- bg
- de
- el
- es
- fr
- hi
- ru
- sw
- th
- tr
- ur
- vi
- zh
thumbnail: https://huggingface.co/front/thumbnails/microsoft.png
tags:
- text-classification
license: mit
---
## MiniLM: Small and Fast Pre-trained Models for Language Understanding and Generation
Mi... | 6,289 | [
[
-0.048004150390625,
-0.035888671875,
0.01276397705078125,
0.009033203125,
0.0001055598258972168,
0.0020046234130859375,
-0.0180206298828125,
-0.0281982421875,
0.007717132568359375,
0.00397491455078125,
-0.0562744140625,
-0.0297698974609375,
-0.036956787109375,
... |
Bingsu/my-korean-stable-diffusion-v1-5 | 2023-05-17T10:14:35.000Z | [
"diffusers",
"safetensors",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"ko",
"license:creativeml-openrail-m",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | Bingsu | null | null | Bingsu/my-korean-stable-diffusion-v1-5 | 17 | 10,350 | diffusers | 2022-11-09T01:28:33 | ---
license: creativeml-openrail-m
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
inference: true
language: ko
---
# my-korean-stable-diffusion-v1-5
It's [runwayml/stable-diffusion-v1-5](https://huggingface.co/runwayml/stable-diffusion-v1-5) model, just text encoder and tokenizer are replaced w... | 6,544 | [
[
-0.025238037109375,
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0.002162933349609375,
0.023162841796875,
-0.02618408203125,
-0.0386962890625,
-0.04931640625,
-0.00... |
aari1995/German_Semantic_STS_V2 | 2023-06-29T11:39:00.000Z | [
"sentence-transformers",
"pytorch",
"safetensors",
"bert",
"gBERT-large",
"feature-extraction",
"sentence-similarity",
"transformers",
"de",
"dataset:stsb_multi_mt",
"endpoints_compatible",
"region:us"
] | sentence-similarity | aari1995 | null | null | aari1995/German_Semantic_STS_V2 | 26 | 10,316 | sentence-transformers | 2022-11-17T09:57:45 | ---
pipeline_tag: sentence-similarity
language:
- de
datasets:
- stsb_multi_mt
tags:
- gBERT-large
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# German_Semantic_STS_V2
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 1024 di... | 5,675 | [
[
-0.020599365234375,
-0.06463623046875,
0.028472900390625,
0.019256591796875,
-0.023712158203125,
-0.034423828125,
-0.0251007080078125,
-0.0047760009765625,
0.01299285888671875,
0.0296783447265625,
-0.04833984375,
-0.050811767578125,
-0.059600830078125,
0.000... |
Undi95/Emerhyst-13B | 2023-09-27T15:23:59.000Z | [
"transformers",
"safetensors",
"llama",
"text-generation",
"not-for-all-audiences",
"nsfw",
"license:cc-by-nc-4.0",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | Undi95 | null | null | Undi95/Emerhyst-13B | 7 | 10,299 | transformers | 2023-09-27T14:24:50 | ---
license: cc-by-nc-4.0
tags:
- not-for-all-audiences
- nsfw
---
13B version of [Undi95/Emerhyst-20B](https://huggingface.co/Undi95/Emerhyst-20B), consider using the 20B if you have the power to. T... | 1,733 | [
[
-0.055206298828125,
-0.055999755859375,
0.03375244140625,
0.037078857421875,
-0.032745361328125,
-0.0135040283203125,
-0.011383056640625,
-0.042236328125,
0.0550537109375,
0.041473388671875,
-0.0570068359375,
-0.01629638671875,
-0.037200927734375,
0.02178955... |
pythainlp/thainer-corpus-v2-base-model | 2023-03-23T07:31:21.000Z | [
"transformers",
"pytorch",
"safetensors",
"camembert",
"token-classification",
"th",
"dataset:pythainlp/thainer-corpus-v2",
"license:cc-by-4.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | token-classification | pythainlp | null | null | pythainlp/thainer-corpus-v2-base-model | 10 | 10,293 | transformers | 2023-03-22T18:03:03 | ---
license: cc-by-4.0
datasets:
- pythainlp/thainer-corpus-v2
language:
- th
metrics:
- f1
widget:
- text: "ฉันชื่อ นางสาวมะลิวา บุญสระดี อาศัยอยู่ที่อำเภอนางรอง จังหวัดบุรีรัมย์ อายุ 23 ปี เพิ่งเรียนจบจาก มหาวิทยาลัยขอนแก่น และนี่คือข้อมูลปลอม ชื่อคนไม่มีอยู่จริง"
---
This is a Named Entity Recognition model that tr... | 4,022 | [
[
-0.03192138671875,
-0.029937744140625,
0.01222991943359375,
0.022613525390625,
-0.0237884521484375,
-0.0084075927734375,
-0.0110321044921875,
-0.0280914306640625,
0.04034423828125,
0.01397705078125,
-0.0269927978515625,
-0.050201416015625,
-0.04461669921875,
... |
microsoft/infoxlm-base | 2021-08-04T11:42:14.000Z | [
"transformers",
"pytorch",
"xlm-roberta",
"fill-mask",
"arxiv:2007.07834",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | microsoft | null | null | microsoft/infoxlm-base | 5 | 10,291 | transformers | 2022-03-02T23:29:05 | # InfoXLM
**InfoXLM** (NAACL 2021, [paper](https://arxiv.org/pdf/2007.07834.pdf), [repo](https://github.com/microsoft/unilm/tree/master/infoxlm), [model](https://huggingface.co/microsoft/infoxlm-base)) InfoXLM: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training.
**MD5**
```
b9d214025837... | 1,246 | [
[
-0.03204345703125,
-0.050994873046875,
0.0117340087890625,
0.035919189453125,
-0.01309967041015625,
0.0177459716796875,
-0.0118255615234375,
-0.0330810546875,
0.011138916015625,
0.02471923828125,
-0.04168701171875,
-0.048492431640625,
-0.03192138671875,
-0.0... |
microsoft/BiomedCLIP-PubMedBERT_256-vit_base_patch16_224 | 2023-05-29T18:39:06.000Z | [
"open_clip",
"clip",
"biology",
"medical",
"zero-shot-image-classification",
"en",
"arxiv:2303.00915",
"license:mit",
"has_space",
"region:us"
] | zero-shot-image-classification | microsoft | null | null | microsoft/BiomedCLIP-PubMedBERT_256-vit_base_patch16_224 | 93 | 10,287 | open_clip | 2023-04-05T19:57:59 | ---
language: en
tags:
- clip
- biology
- medical
license: mit
library_name: open_clip
widget:
- src: >-
https://huggingface.co/microsoft/BiomedCLIP-PubMedBERT_256-vit_base_patch16_224/resolve/main/example_data/biomed_image_classification_example_data/squamous_cell_carcinoma_histopathology.jpeg
candidate_la... | 4,134 | [
[
-0.02093505859375,
-0.03509521484375,
0.04461669921875,
0.005340576171875,
-0.034637451171875,
-0.0013093948364257812,
-0.0064849853515625,
-0.04339599609375,
0.015899658203125,
0.0343017578125,
-0.032989501953125,
-0.053985595703125,
-0.049072265625,
0.0144... |
kandinsky-community/kandinsky-2-1-prior | 2023-10-09T11:32:58.000Z | [
"diffusers",
"kandinsky",
"license:apache-2.0",
"has_space",
"diffusers:KandinskyPriorPipeline",
"region:us"
] | null | kandinsky-community | null | null | kandinsky-community/kandinsky-2-1-prior | 10 | 10,277 | diffusers | 2023-05-24T09:51:57 | ---
license: apache-2.0
tags:
- kandinsky
inference: false
---
# Kandinsky 2.1
Kandinsky 2.1 inherits best practices from Dall-E 2 and Latent diffusion while introducing some new ideas.
It uses the CLIP model as a text and image encoder, and diffusion image prior (mapping) between latent spaces of CLIP modalities. ... | 8,454 | [
[
-0.0313720703125,
-0.051910400390625,
0.03302001953125,
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-0.002716064453125,
-0.02496337890625,
0.00829315185546875,
0.033782958984375,
-0.0283660888671875,
-0.033203125,
-0.04083251953125,
-0.0... |
cerebras/Cerebras-GPT-1.3B | 2023-04-07T13:50:30.000Z | [
"transformers",
"pytorch",
"gpt2",
"causal-lm",
"text-generation",
"en",
"dataset:the_pile",
"arxiv:2304.03208",
"arxiv:2203.15556",
"arxiv:2101.00027",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | cerebras | null | null | cerebras/Cerebras-GPT-1.3B | 44 | 10,255 | transformers | 2023-03-20T20:43:21 | ---
language:
- en
tags:
- pytorch
- causal-lm
license: apache-2.0
datasets:
- the_pile
pipeline_tag: text-generation
---
# Cerebras-GPT 1.3B
Check out our [Blog Post](https://www.cerebras.net/cerebras-gpt) and [arXiv paper](https://arxiv.org/abs/2304.03208)!
## Model Description
The Cerebras-GPT family is released ... | 12,559 | [
[
-0.02752685546875,
-0.048004150390625,
0.0184326171875,
0.0135650634765625,
-0.0196075439453125,
-0.01532745361328125,
-0.01537322998046875,
-0.031890869140625,
0.013580322265625,
0.02130126953125,
-0.02911376953125,
-0.030975341796875,
-0.055450439453125,
-... |
vilm/vietcuna-7b-v3 | 2023-08-10T08:54:56.000Z | [
"transformers",
"pytorch",
"safetensors",
"bloom",
"text-generation",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | vilm | null | null | vilm/vietcuna-7b-v3 | 7 | 10,249 | transformers | 2023-08-05T10:48:56 | Vietcuna-7B v3.0
Prompt Template:
```
Một cuộc trò chuyện giữa một người dùng tò mò và một trợ lý trí tuệ nhân tạo. Trợ lý đưa ra các câu trả lời hữu ích, chi tiết và lịch sự cho các câu hỏi của người dùng.\n\n### Human: {human_message}\n\n### Assistant:"
``` | 260 | [
[
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0.03765869140625,
0.049041748046875,
-0.03717041015625,
-0.042694091796875,
-0.0165252685546875,
... |
google/vivit-b-16x2-kinetics400 | 2023-08-03T10:01:22.000Z | [
"transformers",
"pytorch",
"vivit",
"vision",
"video-classification",
"arxiv:2103.15691",
"license:mit",
"endpoints_compatible",
"has_space",
"region:us"
] | video-classification | google | null | null | google/vivit-b-16x2-kinetics400 | 6 | 10,222 | transformers | 2022-11-23T21:21:55 | ---
license: "mit"
tags:
- vision
- video-classification
---
# ViViT (Video Vision Transformer)
ViViT model as introduced in the paper [ViViT: A Video Vision Transformer](https://arxiv.org/abs/2103.15691) by Arnab et al. and first released in [this repository](https://github.com/google-research/scenic/tree/main/scen... | 1,405 | [
[
-0.042388916015625,
-0.044189453125,
0.0146026611328125,
0.0045623779296875,
-0.041412353515625,
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0.01171875,
-0.018890380859375,
0.0266876220703125,
0.0291748046875,
-0.05999755859375,
-0.0191650390625,
-0.05029296875,
-0.031051635742187... |
yujiepan/llama-2-tiny-random | 2023-08-21T06:18:39.000Z | [
"transformers",
"pytorch",
"openvino",
"llama",
"text-generation",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | yujiepan | null | null | yujiepan/llama-2-tiny-random | 0 | 10,192 | transformers | 2023-08-21T05:31:01 | ---
pipeline_tag: text-generation
inference: true
widget:
- text: 'Hello!'
example_title: Hello world
group: Python
library_name: transformers
---
# yujiepan/llama-2-tiny-random
This model is **randomly initialized**, using the config from [meta-llama/Llama-2-7b-chat-hf](https://huggingface.co/yujiepan/llama-2-ti... | 537 | [
[
-0.028106689453125,
-0.05902099609375,
0.04290771484375,
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-0.051849365234375,
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-0.00019252300262451172,
-0.039581298828125,
0.0458984375,
0.04449462890625,
-0.06524658203125,
-0.0243377685546875,
-0.047271728515625,
0.0... |
timm/vit_base_patch8_224.dino | 2023-05-06T03:20:58.000Z | [
"timm",
"pytorch",
"safetensors",
"image-classification",
"arxiv:2104.14294",
"arxiv:2010.11929",
"license:apache-2.0",
"region:us"
] | image-classification | timm | null | null | timm/vit_base_patch8_224.dino | 0 | 10,189 | timm | 2022-12-22T07:23:57 | ---
tags:
- image-classification
- timm
library_name: timm
license: apache-2.0
---
# Model card for vit_base_patch8_224.dino
A Vision Transformer (ViT) image feature model. Trained with Self-Supervised DINO method.
## Model Details
- **Model Type:** Image classification / feature backbone
- **Model Stats:**
- Para... | 3,675 | [
[
-0.04132080078125,
-0.0231475830078125,
0.0051727294921875,
0.012054443359375,
-0.026641845703125,
-0.0244293212890625,
-0.0190582275390625,
-0.038726806640625,
0.0230255126953125,
0.026519775390625,
-0.036407470703125,
-0.0380859375,
-0.050140380859375,
0.0... |
dbmdz/bert-base-turkish-128k-uncased | 2021-05-19T15:13:16.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"bert",
"tr",
"license:mit",
"endpoints_compatible",
"has_space",
"region:us"
] | null | dbmdz | null | null | dbmdz/bert-base-turkish-128k-uncased | 11 | 10,165 | transformers | 2022-03-02T23:29:05 | ---
language: tr
license: mit
---
# 🤗 + 📚 dbmdz Turkish BERT model
In this repository the MDZ Digital Library team (dbmdz) at the Bavarian State
Library open sources an uncased model for Turkish 🎉
# 🇹🇷 BERTurk
BERTurk is a community-driven uncased BERT model for Turkish.
Some datasets used for pretraining and... | 2,963 | [
[
-0.037933349609375,
-0.0521240234375,
0.00841522216796875,
0.01904296875,
-0.0343017578125,
-0.0193939208984375,
-0.0289154052734375,
-0.0328369140625,
0.0191650390625,
0.0291595458984375,
-0.0428466796875,
-0.04998779296875,
-0.05255126953125,
-0.0085830688... |
stabilityai/stablelm-tuned-alpha-3b | 2023-04-19T12:38:16.000Z | [
"transformers",
"pytorch",
"gpt_neox",
"text-generation",
"causal-lm",
"en",
"dataset:dmayhem93/ChatCombined",
"dataset:tatsu-lab/alpaca",
"dataset:nomic-ai/gpt4all_prompt_generations",
"dataset:Dahoas/full-hh-rlhf",
"dataset:jeffwan/sharegpt_vicuna",
"dataset:HuggingFaceH4/databricks_dolly_15... | text-generation | stabilityai | null | null | stabilityai/stablelm-tuned-alpha-3b | 106 | 10,163 | transformers | 2023-04-19T02:10:24 | ---
language:
- en
tags:
- causal-lm
license:
- cc-by-nc-sa-4.0
datasets:
- dmayhem93/ChatCombined
- tatsu-lab/alpaca
- nomic-ai/gpt4all_prompt_generations
- Dahoas/full-hh-rlhf
- jeffwan/sharegpt_vicuna
- HuggingFaceH4/databricks_dolly_15k
---
# StableLM-Tuned-Alpha
## Model Description
`StableLM-Tuned-Alpha` is a... | 7,242 | [
[
-0.033782958984375,
-0.07733154296875,
0.01001739501953125,
0.013702392578125,
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0.016265869140625,
-0.039459228515625,
-0.04510498046875,
-0.040802001953125,
0.... |
RWKV/rwkv-4-169m-pile | 2023-05-15T09:59:20.000Z | [
"transformers",
"pytorch",
"rwkv",
"text-generation",
"dataset:EleutherAI/pile",
"endpoints_compatible",
"has_space",
"region:us"
] | text-generation | RWKV | null | null | RWKV/rwkv-4-169m-pile | 6 | 10,163 | transformers | 2023-05-04T13:36:31 | ---
datasets:
- EleutherAI/pile
---
# Model card for RWKV-4 | 169M parameters trained on Pile dataset
RWKV is a project led by [Bo Peng](https://github.com/BlinkDL). Learn more about the model archit... | 5,303 | [
[
-0.029052734375,
-0.04339599609375,
-0.001171112060546875,
0.013092041015625,
-0.018524169921875,
-0.024017333984375,
-0.01085662841796875,
-0.0231475830078125,
-0.006221771240234375,
0.0188140869140625,
-0.04022216796875,
-0.0257720947265625,
-0.037139892578125... |
facebook/dinov2-large | 2023-09-06T11:23:50.000Z | [
"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-large | 11 | 10,162 | transformers | 2023-07-17T16:47:01 | ---
license: apache-2.0
tags:
- dino
- vision
---
# Vision Transformer (large-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,
-0.031280517578125,
0.0084381103515625,
-0.0081787109375,
-0.035980224609375,
-0.00362396240234375,
0.006282806396484375,
-0.031585693359375,
0.0206146240234375,
0.038238525390625,
-0.033843994140625,
-0.0174102783203125,
-0.051849365234375,
... |
facebook/mbart-large-en-ro | 2023-09-11T13:45:59.000Z | [
"transformers",
"pytorch",
"tf",
"safetensors",
"mbart",
"translation",
"en",
"ro",
"license:mit",
"endpoints_compatible",
"has_space",
"region:us"
] | translation | facebook | null | null | facebook/mbart-large-en-ro | 0 | 10,151 | transformers | 2022-03-02T23:29:05 | ---
tags:
- translation
language:
- en
- ro
license: mit
---
### mbart-large-en-ro
This is mbart-large-cc25, finetuned on wmt_en_ro.
It scores BLEU 28.1 without post processing and BLEU 38 with postprocessing. Instructions in `romanian_postprocessing.md`
Original Code: https://github.com/pytorch/fairseq/tree/master... | 476 | [
[
-0.043426513671875,
-0.050506591796875,
0.00873565673828125,
0.03466796875,
-0.033294677734375,
-0.0210723876953125,
-0.023468017578125,
-0.019439697265625,
0.014068603515625,
0.029754638671875,
-0.060150146484375,
-0.033233642578125,
-0.03741455078125,
-0.0... |
timm/convnext_tiny.fb_in22k | 2023-03-31T22:37:49.000Z | [
"timm",
"pytorch",
"safetensors",
"image-classification",
"dataset:imagenet-22k",
"arxiv:2201.03545",
"license:apache-2.0",
"region:us"
] | image-classification | timm | null | null | timm/convnext_tiny.fb_in22k | 0 | 10,149 | timm | 2022-12-13T07:14:47 | ---
tags:
- image-classification
- timm
library_tag: timm
license: apache-2.0
datasets:
- imagenet-22k
---
# Model card for convnext_tiny.fb_in22k
A ConvNeXt image classification model. Pretrained on ImageNet-22k by paper authors.
## Model Details
- **Model Type:** Image classification / feature backbone
- **Model S... | 15,596 | [
[
-0.0665283203125,
-0.03302001953125,
-0.002605438232421875,
0.036865234375,
-0.0311279296875,
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-0.013427734375,
-0.035308837890625,
0.06561279296875,
0.0163726806640625,
-0.043304443359375,
-0.0404052734375,
-0.05010986328125,
-0.0029373... |
bigcode/starcoderbase | 2023-05-11T08:10:58.000Z | [
"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/starcoderbase | 355 | 10,142 | transformers | 2023-05-03T15:16:10 | ---
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: StarCoderBase
results:
- task:
... | 11,049 | [
[
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0.0227203369140625,
-0.040618896484375,
-0.032684326171875,
-0.05859375,
0.002996444... |
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