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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
microsoft/BiomedNLP-KRISSBERT-PubMed-UMLS-EL | 2022-05-25T02:45:36.000Z | [
"transformers",
"pytorch",
"bert",
"exbert",
"feature-extraction",
"en",
"arxiv:2112.07887",
"license:mit",
"endpoints_compatible",
"region:us"
] | feature-extraction | microsoft | null | null | microsoft/BiomedNLP-KRISSBERT-PubMed-UMLS-EL | 18 | 2,686 | transformers | 2022-04-15T17:50:38 | ---
language: en
tags:
- exbert
license: mit
pipeline_tag: feature-extraction
widget:
- text: "<ENT> ER </ENT> crowding has become a wide-spread problem."
---
## KRISSBERT
[https://arxiv.org/pdf/2112.07887.pdf](https://arxiv.org/pdf/2112.07887.pdf)
Entity linking faces significant challenges such as prolific variati... | 4,545 | [
[
-0.02252197265625,
-0.056182861328125,
0.055755615234375,
-0.005096435546875,
-0.00872802734375,
-0.0186767578125,
-0.00905609130859375,
-0.05560302734375,
0.037750244140625,
0.0269012451171875,
-0.022796630859375,
-0.051849365234375,
-0.03472900390625,
0.03... |
Yntec/NeverEndingDream768 | 2023-09-01T10:36:27.000Z | [
"diffusers",
"stable-diffusion",
"text-to-image",
"art",
"artistic",
"Lykon",
"en",
"license:other",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | Yntec | null | null | Yntec/NeverEndingDream768 | 0 | 2,686 | diffusers | 2023-09-01T09:01:53 | ---
language:
- en
license: other
library_name: diffusers
pipeline_tag: text-to-image
tags:
- stable-diffusion
- text-to-image
- art
- artistic
- Lykon
---
# Never Ending Dream 768
768x768 version of this model for the interference API.
Also consider supporting Lykon on Patreon
- https://www.patreon.com/Lykon275
S... | 704 | [
[
-0.0282135009765625,
-0.03741455078125,
0.0479736328125,
0.0244293212890625,
-0.021331787109375,
0.009185791015625,
0.01482391357421875,
-0.07281494140625,
0.058868408203125,
0.060028076171875,
-0.06768798828125,
-0.041900634765625,
-0.0369873046875,
-0.0075... |
keremberke/yolov8n-painting-classification | 2023-02-22T13:01:15.000Z | [
"ultralytics",
"tensorboard",
"v8",
"ultralyticsplus",
"yolov8",
"yolo",
"vision",
"image-classification",
"pytorch",
"awesome-yolov8-models",
"dataset:keremberke/painting-style-classification",
"model-index",
"region:us"
] | image-classification | keremberke | null | null | keremberke/yolov8n-painting-classification | 0 | 2,685 | ultralytics | 2023-01-27T16:49:23 |
---
tags:
- ultralyticsplus
- yolov8
- ultralytics
- yolo
- vision
- image-classification
- pytorch
- awesome-yolov8-models
library_name: ultralytics
library_version: 8.0.21
inference: false
datasets:
- keremberke/painting-style-classification
model-index:
- name: keremberke/yolov8n-painting-classification
result... | 2,262 | [
[
-0.0369873046875,
-0.0230865478515625,
0.03521728515625,
-0.012451171875,
-0.0233001708984375,
-0.0044708251953125,
0.0038280487060546875,
-0.03424072265625,
0.01328277587890625,
0.02813720703125,
-0.0278472900390625,
-0.0452880859375,
-0.04315185546875,
-0.... |
nvidia/mit-b3 | 2022-08-06T10:24:57.000Z | [
"transformers",
"pytorch",
"tf",
"segformer",
"image-classification",
"vision",
"dataset:imagenet_1k",
"arxiv:2105.15203",
"license:other",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | image-classification | nvidia | null | null | nvidia/mit-b3 | 2 | 2,684 | transformers | 2022-03-02T23:29:05 | ---
license: other
tags:
- vision
datasets:
- imagenet_1k
widget:
- src: https://huggingface.co/datasets/hf-internal-testing/fixtures_ade20k/resolve/main/ADE_val_00000001.jpg
example_title: House
- src: https://huggingface.co/datasets/hf-internal-testing/fixtures_ade20k/resolve/main/ADE_val_00000002.jpg
example_tit... | 3,354 | [
[
-0.06805419921875,
-0.05224609375,
0.00667572021484375,
0.01226043701171875,
-0.02508544921875,
-0.0269927978515625,
0.003635406494140625,
-0.049041748046875,
0.0177154541015625,
0.0440673828125,
-0.059722900390625,
-0.03985595703125,
-0.057098388671875,
0.0... |
EleutherAI/polyglot-ko-3.8b | 2023-06-07T05:03:23.000Z | [
"transformers",
"pytorch",
"safetensors",
"gpt_neox",
"text-generation",
"causal-lm",
"ko",
"arxiv:2104.09864",
"arxiv:2204.04541",
"arxiv:2306.02254",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | EleutherAI | null | null | EleutherAI/polyglot-ko-3.8b | 19 | 2,684 | transformers | 2022-09-09T14:15:36 | ---
language:
- ko
tags:
- pytorch
- causal-lm
license: apache-2.0
---
# Polyglot-Ko-3.8B
## Model Description
Polyglot-Ko is a series of large-scale Korean autoregressive language models made by the EleutherAI polyglot team.
| Hyperparameter | Value ... | 15,475 | [
[
-0.049163818359375,
-0.051849365234375,
0.021270751953125,
0.00511932373046875,
-0.038177490234375,
0.0007643699645996094,
-0.00862884521484375,
-0.04022216796875,
0.031280517578125,
0.01335906982421875,
-0.033966064453125,
-0.0489501953125,
-0.05426025390625,
... |
keremberke/yolov8n-shoe-classification | 2023-02-22T13:05:06.000Z | [
"ultralytics",
"tensorboard",
"v8",
"ultralyticsplus",
"yolov8",
"yolo",
"vision",
"image-classification",
"pytorch",
"awesome-yolov8-models",
"dataset:keremberke/shoe-classification",
"model-index",
"region:us"
] | image-classification | keremberke | null | null | keremberke/yolov8n-shoe-classification | 0 | 2,684 | ultralytics | 2023-01-29T11:51:08 |
---
tags:
- ultralyticsplus
- yolov8
- ultralytics
- yolo
- vision
- image-classification
- pytorch
- awesome-yolov8-models
library_name: ultralytics
library_version: 8.0.23
inference: false
datasets:
- keremberke/shoe-classification
model-index:
- name: keremberke/yolov8n-shoe-classification
results:
- task:
... | 1,761 | [
[
-0.032196044921875,
-0.0144500732421875,
0.030242919921875,
-0.010467529296875,
-0.038665771484375,
-0.01126861572265625,
-0.0007877349853515625,
-0.042816162109375,
0.010040283203125,
0.007518768310546875,
-0.036163330078125,
-0.045989990234375,
-0.039459228515... |
keremberke/yolov8n-valorant-detection | 2023-02-22T13:02:22.000Z | [
"ultralytics",
"tensorboard",
"v8",
"ultralyticsplus",
"yolov8",
"yolo",
"vision",
"object-detection",
"pytorch",
"awesome-yolov8-models",
"dataset:keremberke/valorant-object-detection",
"model-index",
"region:us"
] | object-detection | keremberke | null | null | keremberke/yolov8n-valorant-detection | 1 | 2,683 | ultralytics | 2023-01-28T08:44:49 |
---
tags:
- ultralyticsplus
- yolov8
- ultralytics
- yolo
- vision
- object-detection
- pytorch
- awesome-yolov8-models
library_name: ultralytics
library_version: 8.0.21
inference: false
datasets:
- keremberke/valorant-object-detection
model-index:
- name: keremberke/yolov8n-valorant-detection
results:
- task:
... | 1,860 | [
[
-0.031341552734375,
-0.0264129638671875,
0.03179931640625,
-0.01436614990234375,
-0.022979736328125,
-0.0146331787109375,
0.01050567626953125,
-0.026763916015625,
0.030181884765625,
0.01532745361328125,
-0.044464111328125,
-0.051971435546875,
-0.03179931640625,
... |
theintuitiveye/HARDblend | 2023-08-24T12:44:24.000Z | [
"diffusers",
"stable-diffusion",
"text-to-image",
"art",
"en",
"license:creativeml-openrail-m",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | theintuitiveye | null | null | theintuitiveye/HARDblend | 79 | 2,681 | diffusers | 2023-02-01T11:10:05 | ---
title: HARDblend
colorFrom: green
colorTo: indigo
sdk: gradio
sdk_version: 3.11.0
pinned: false
license: creativeml-openrail-m
tags:
- stable-diffusion
- text-to-image
- art
inference: true
language:
- en
library_name: diffusers
---
# **HARDblend**
A versatile photorealistic NSFW capable model which is great at gen... | 2,173 | [
[
-0.0318603515625,
-0.035186767578125,
0.030914306640625,
0.0303192138671875,
-0.0184326171875,
-0.033233642578125,
0.004665374755859375,
-0.02581787109375,
-0.0017957687377929688,
0.06622314453125,
-0.05975341796875,
-0.0574951171875,
-0.038909912109375,
-0.... |
vesteinn/vit-mae-cub | 2023-08-01T08:28:42.000Z | [
"transformers",
"pytorch",
"safetensors",
"vit",
"image-classification",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | image-classification | vesteinn | null | null | vesteinn/vit-mae-cub | 0 | 2,681 | transformers | 2023-07-24T13:12:26 | Note that this model does not work directly with HF, a modification that does mean pooling before the layernorm and classification head is needed.
```python
from transformers import (
ViTForImageClassification,
pipeline,
AutoImageProcessor,
ViTConfig,
ViTModel,
)
from transformers.modeling_output... | 6,052 | [
[
-0.039093017578125,
-0.037689208984375,
0.0175018310546875,
0.01474761962890625,
-0.0212249755859375,
-0.018035888671875,
-0.00540924072265625,
-0.01360321044921875,
0.01593017578125,
0.024810791015625,
-0.04669189453125,
-0.03912353515625,
-0.062286376953125,
... |
ramsrigouthamg/t5_paraphraser | 2020-12-11T22:00:04.000Z | [
"transformers",
"pytorch",
"t5",
"text2text-generation",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text2text-generation | ramsrigouthamg | null | null | ramsrigouthamg/t5_paraphraser | 11 | 2,680 | transformers | 2022-03-02T23:29:05 | ## Model in Action 🚀
```python
import torch
from transformers import T5ForConditionalGeneration,T5Tokenizer
def set_seed(seed):
torch.manual_seed(seed)
if torch.cuda.is_available():
torch.cuda.manual_seed_all(seed)
set_seed(42)
model = T5ForConditionalGeneration.from_pretrained('ramsrigouthamg/t5_paraphra... | 2,598 | [
[
-0.016845703125,
-0.06036376953125,
0.03472900390625,
0.004909515380859375,
-0.0140228271484375,
0.0118408203125,
-0.0046234130859375,
-0.0002663135528564453,
-0.0096893310546875,
0.03326416015625,
-0.0438232421875,
-0.0445556640625,
-0.0447998046875,
0.0157... |
keremberke/yolov8s-pokemon-classification | 2023-02-22T13:02:11.000Z | [
"ultralytics",
"tensorboard",
"v8",
"ultralyticsplus",
"yolov8",
"yolo",
"vision",
"image-classification",
"pytorch",
"awesome-yolov8-models",
"dataset:keremberke/pokemon-classification",
"model-index",
"region:us"
] | image-classification | keremberke | null | null | keremberke/yolov8s-pokemon-classification | 0 | 2,678 | ultralytics | 2023-01-28T04:48:41 |
---
tags:
- ultralyticsplus
- yolov8
- ultralytics
- yolo
- vision
- image-classification
- pytorch
- awesome-yolov8-models
library_name: ultralytics
library_version: 8.0.21
inference: false
datasets:
- keremberke/pokemon-classification
model-index:
- name: keremberke/yolov8s-pokemon-classification
results:
- t... | 3,000 | [
[
-0.03936767578125,
-0.01153564453125,
0.01904296875,
-0.005725860595703125,
-0.00901031494140625,
0.0141448974609375,
0.0126953125,
-0.02197265625,
0.040435791015625,
0.0163116455078125,
-0.0267181396484375,
-0.037567138671875,
-0.047821044921875,
0.01763916... |
livingbox/model-test-oct-23 | 2023-10-24T19:23:32.000Z | [
"diffusers",
"text-to-image",
"stable-diffusion",
"license:creativeml-openrail-m",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"region:us",
"has_space"
] | text-to-image | livingbox | null | null | livingbox/model-test-oct-23 | 0 | 2,678 | diffusers | 2023-10-24T19:17:58 | ---
license: creativeml-openrail-m
tags:
- text-to-image
- stable-diffusion
---
### Model-test-oct-23 Dreambooth model trained by livingbox with [TheLastBen's fast-DreamBooth](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast-DreamBooth.ipynb) notebook
Test the concept via A1111... | 508 | [
[
-0.033782958984375,
-0.0740966796875,
0.034332275390625,
0.034912109375,
-0.0268402099609375,
0.033538818359375,
0.032379150390625,
-0.0294342041015625,
0.0472412109375,
0.00872039794921875,
-0.029693603515625,
-0.01983642578125,
-0.022796630859375,
-0.00427... |
ilovebots/bert-sdg-french | 2023-08-11T17:57:30.000Z | [
"transformers",
"pytorch",
"safetensors",
"bert",
"text-classification",
"Objectifs de développement durable (ODD)",
"SDG",
"BERT Classification",
"fr",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-classification | ilovebots | null | null | ilovebots/bert-sdg-french | 0 | 2,677 | transformers | 2023-08-03T22:00:26 | ---
license: mit
language:
- fr
tags:
- Objectifs de développement durable (ODD)
- SDG
- BERT Classification
---
# ilovebots/bert-sdg-french
<!-- Provide a quick summary of what the model is/does. -->
Ce modèle permet de classer les textes en fonction des objectifs de développement durable (ODD) des Nations Unies.
... | 3,169 | [
[
-0.043182373046875,
-0.04986572265625,
0.0251617431640625,
0.014068603515625,
-0.0270233154296875,
-0.01490020751953125,
-0.010986328125,
-0.0291595458984375,
0.0118255615234375,
0.027496337890625,
-0.046722412109375,
-0.04730224609375,
-0.056243896484375,
0... |
pszemraj/led-base-book-summary | 2023-10-05T06:57:14.000Z | [
"transformers",
"pytorch",
"safetensors",
"led",
"text2text-generation",
"summarization",
"summary",
"longformer",
"booksum",
"long-document",
"long-form",
"dataset:kmfoda/booksum",
"license:apache-2.0",
"license:bsd-3-clause",
"model-index",
"autotrain_compatible",
"endpoints_compat... | summarization | pszemraj | null | null | pszemraj/led-base-book-summary | 41 | 2,675 | transformers | 2022-03-02T23:29:05 | ---
license:
- apache-2.0
- bsd-3-clause
tags:
- summarization
- led
- summary
- longformer
- booksum
- long-document
- long-form
datasets:
- kmfoda/booksum
metrics:
- rouge
widget:
- text: large earthquakes along a given fault segment do not occur at random intervals
because it takes time to accumulate the strain ... | 32,335 | [
[
-0.020111083984375,
-0.049560546875,
0.02099609375,
0.0188446044921875,
-0.035064697265625,
-0.005268096923828125,
-0.030914306640625,
-0.0166778564453125,
0.0217742919921875,
0.0311737060546875,
-0.02569580078125,
-0.04876708984375,
-0.03900146484375,
0.022... |
timm/vit_base_patch16_rpn_224.sw_in1k | 2023-05-06T00:03:08.000Z | [
"timm",
"pytorch",
"safetensors",
"image-classification",
"dataset:imagenet-1k",
"arxiv:2111.09883",
"arxiv:2010.11929",
"license:apache-2.0",
"region:us"
] | image-classification | timm | null | null | timm/vit_base_patch16_rpn_224.sw_in1k | 0 | 2,675 | timm | 2022-12-22T07:31:51 | ---
tags:
- image-classification
- timm
library_name: timm
license: apache-2.0
datasets:
- imagenet-1k
---
# Model card for vit_base_patch16_rpn_224.sw_in1k
A Vision Transformer (ViT) image classification model. This is a `timm` specific variation of the architecture with residual post normalization blocks. Trained on... | 4,086 | [
[
-0.038055419921875,
-0.0269012451171875,
-0.005771636962890625,
0.01377105712890625,
-0.028045654296875,
-0.0287628173828125,
-0.0209197998046875,
-0.038482666015625,
0.016571044921875,
0.0305938720703125,
-0.041534423828125,
-0.03778076171875,
-0.05191040039062... |
keremberke/yolov8n-plane-detection | 2023-02-22T13:03:17.000Z | [
"ultralytics",
"tensorboard",
"v8",
"ultralyticsplus",
"yolov8",
"yolo",
"vision",
"object-detection",
"pytorch",
"awesome-yolov8-models",
"dataset:keremberke/plane-detection",
"model-index",
"region:us"
] | object-detection | keremberke | null | null | keremberke/yolov8n-plane-detection | 2 | 2,675 | ultralytics | 2023-01-29T06:22:06 |
---
tags:
- ultralyticsplus
- yolov8
- ultralytics
- yolo
- vision
- object-detection
- pytorch
- awesome-yolov8-models
library_name: ultralytics
library_version: 8.0.21
inference: false
datasets:
- keremberke/plane-detection
model-index:
- name: keremberke/yolov8n-plane-detection
results:
- task:
type: o... | 1,771 | [
[
-0.038665771484375,
-0.0206451416015625,
0.040130615234375,
-0.0159149169921875,
-0.02630615234375,
-0.02044677734375,
0.019561767578125,
-0.025604248046875,
0.02728271484375,
0.020355224609375,
-0.044281005859375,
-0.044677734375,
-0.0275421142578125,
-0.01... |
keremberke/yolov8s-plane-detection | 2023-02-22T13:03:24.000Z | [
"ultralytics",
"tensorboard",
"v8",
"ultralyticsplus",
"yolov8",
"yolo",
"vision",
"object-detection",
"pytorch",
"awesome-yolov8-models",
"dataset:keremberke/plane-detection",
"model-index",
"region:us"
] | object-detection | keremberke | null | null | keremberke/yolov8s-plane-detection | 3 | 2,675 | ultralytics | 2023-01-29T06:42:07 |
---
tags:
- ultralyticsplus
- yolov8
- ultralytics
- yolo
- vision
- object-detection
- pytorch
- awesome-yolov8-models
library_name: ultralytics
library_version: 8.0.21
inference: false
datasets:
- keremberke/plane-detection
model-index:
- name: keremberke/yolov8s-plane-detection
results:
- task:
type: o... | 1,771 | [
[
-0.03826904296875,
-0.019134521484375,
0.0413818359375,
-0.01654052734375,
-0.02667236328125,
-0.0194854736328125,
0.0196533203125,
-0.0252838134765625,
0.0263824462890625,
0.0193328857421875,
-0.043304443359375,
-0.044647216796875,
-0.028350830078125,
-0.01... |
keremberke/yolov8s-pcb-defect-segmentation | 2023-02-22T13:02:28.000Z | [
"ultralytics",
"tensorboard",
"v8",
"ultralyticsplus",
"yolov8",
"yolo",
"vision",
"image-segmentation",
"pytorch",
"awesome-yolov8-models",
"dataset:keremberke/pcb-defect-segmentation",
"model-index",
"region:us"
] | image-segmentation | keremberke | null | null | keremberke/yolov8s-pcb-defect-segmentation | 1 | 2,674 | ultralytics | 2023-01-28T07:39:17 |
---
tags:
- ultralyticsplus
- yolov8
- ultralytics
- yolo
- vision
- image-segmentation
- pytorch
- awesome-yolov8-models
library_name: ultralytics
library_version: 8.0.21
inference: false
datasets:
- keremberke/pcb-defect-segmentation
model-index:
- name: keremberke/yolov8s-pcb-defect-segmentation
results:
- t... | 2,066 | [
[
-0.026153564453125,
-0.03790283203125,
0.049835205078125,
-0.00890350341796875,
-0.0350341796875,
-0.011688232421875,
0.0234527587890625,
-0.034576416015625,
0.02545166015625,
0.01416015625,
-0.051300048828125,
-0.04705810546875,
-0.0208892822265625,
-0.0171... |
Hvijapuram22/my-pet-dog | 2023-11-06T14:01:26.000Z | [
"diffusers",
"NxtWave-GenAI-Webinar",
"text-to-image",
"stable-diffusion",
"license:creativeml-openrail-m",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | Hvijapuram22 | null | null | Hvijapuram22/my-pet-dog | 0 | 2,673 | diffusers | 2023-11-06T13:47:39 | ---
license: creativeml-openrail-m
tags:
- NxtWave-GenAI-Webinar
- text-to-image
- stable-diffusion
---
### My-Pet-Dog Dreambooth model trained by Hvijapuram22 following the "Build your own Gen AI model" session by NxtWave.
Project Submission Code: MITS-1185
Sample pictures of this concept:
![image/png](https://cdn-... | 775 | [
[
-0.06268310546875,
-0.032470703125,
0.02337646484375,
0.0207672119140625,
-0.017303466796875,
0.036712646484375,
0.0206146240234375,
-0.0267333984375,
0.0282745361328125,
0.010101318359375,
-0.039031982421875,
-0.0303802490234375,
-0.0245361328125,
0.0084533... |
deepset/gbert-base-germandpr-question_encoder | 2023-05-05T06:59:31.000Z | [
"transformers",
"pytorch",
"safetensors",
"dpr",
"feature-extraction",
"exbert",
"de",
"dataset:deepset/germandpr",
"license:mit",
"endpoints_compatible",
"region:us"
] | feature-extraction | deepset | null | null | deepset/gbert-base-germandpr-question_encoder | 5 | 2,672 | transformers | 2022-03-02T23:29:05 | ---
language: de
datasets:
- deepset/germandpr
license: mit
thumbnail: https://thumb.tildacdn.com/tild3433-3637-4830-a533-353833613061/-/resize/720x/-/format/webp/germanquad.jpg
tags:
- exbert
---
... | 4,001 | [
[
-0.03619384765625,
-0.06414794921875,
0.0250091552734375,
0.00354766845703125,
-0.007678985595703125,
-0.0199432373046875,
-0.03399658203125,
-0.0261688232421875,
-0.007381439208984375,
0.0255584716796875,
-0.0284576416015625,
-0.04632568359375,
-0.0300750732421... |
keremberke/yolov8s-valorant-detection | 2023-02-22T13:02:34.000Z | [
"ultralytics",
"tensorboard",
"v8",
"ultralyticsplus",
"yolov8",
"yolo",
"vision",
"object-detection",
"pytorch",
"awesome-yolov8-models",
"dataset:keremberke/valorant-object-detection",
"model-index",
"region:us"
] | object-detection | keremberke | null | null | keremberke/yolov8s-valorant-detection | 0 | 2,669 | ultralytics | 2023-01-28T09:17:46 |
---
tags:
- ultralyticsplus
- yolov8
- ultralytics
- yolo
- vision
- object-detection
- pytorch
- awesome-yolov8-models
library_name: ultralytics
library_version: 8.0.21
inference: false
datasets:
- keremberke/valorant-object-detection
model-index:
- name: keremberke/yolov8s-valorant-detection
results:
- task:
... | 1,860 | [
[
-0.0306396484375,
-0.0245819091796875,
0.033172607421875,
-0.0143585205078125,
-0.0234222412109375,
-0.01294708251953125,
0.0113677978515625,
-0.0267181396484375,
0.0297698974609375,
0.01509857177734375,
-0.043792724609375,
-0.05169677734375,
-0.032928466796875,... |
saattrupdan/nbailab-base-ner-scandi | 2023-05-16T13:02:06.000Z | [
"transformers",
"pytorch",
"safetensors",
"bert",
"token-classification",
"da",
"no",
"nb",
"nn",
"sv",
"fo",
"is",
"dataset:dane",
"dataset:norne",
"dataset:wikiann",
"dataset:suc3.0",
"arxiv:1911.12146",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"has_sp... | token-classification | saattrupdan | null | null | saattrupdan/nbailab-base-ner-scandi | 14 | 2,666 | transformers | 2022-03-02T23:29:05 | ---
language:
- da
- no
- nb
- nn
- sv
- fo
- is
license: mit
datasets:
- dane
- norne
- wikiann
- suc3.0
model-index:
- name: nbailab-base-ner-scandi
results: []
widget:
- "Hans er en professor på Københavns Universitetet i København, og han er en rigtig københavner. Hans kat, altså Hans' kat, Lisa, er supersød. Han... | 5,962 | [
[
-0.0501708984375,
-0.0355224609375,
0.0168304443359375,
-0.0009493827819824219,
-0.009368896484375,
-0.00930023193359375,
-0.00652313232421875,
-0.0222930908203125,
0.046630859375,
0.01186370849609375,
-0.036376953125,
-0.048583984375,
-0.03759765625,
0.0082... |
keremberke/yolov8s-csgo-player-detection | 2023-02-22T13:02:50.000Z | [
"ultralytics",
"tensorboard",
"v8",
"ultralyticsplus",
"yolov8",
"yolo",
"vision",
"object-detection",
"pytorch",
"awesome-yolov8-models",
"dataset:keremberke/csgo-object-detection",
"model-index",
"region:us"
] | object-detection | keremberke | null | null | keremberke/yolov8s-csgo-player-detection | 2 | 2,665 | ultralytics | 2023-01-29T01:55:30 |
---
tags:
- ultralyticsplus
- yolov8
- ultralytics
- yolo
- vision
- object-detection
- pytorch
- awesome-yolov8-models
library_name: ultralytics
library_version: 8.0.21
inference: false
datasets:
- keremberke/csgo-object-detection
model-index:
- name: keremberke/yolov8s-csgo-player-detection
results:
- task:
... | 1,835 | [
[
-0.037506103515625,
-0.027496337890625,
0.036285400390625,
-0.0199737548828125,
-0.024749755859375,
-0.00533294677734375,
-0.0007238388061523438,
-0.039398193359375,
0.02178955078125,
0.00931549072265625,
-0.048065185546875,
-0.0419921875,
-0.03106689453125,
... |
timm/convnext_atto_ols.a2_in1k | 2023-03-31T21:54:47.000Z | [
"timm",
"pytorch",
"safetensors",
"image-classification",
"dataset:imagenet-1k",
"arxiv:2201.03545",
"license:apache-2.0",
"region:us"
] | image-classification | timm | null | null | timm/convnext_atto_ols.a2_in1k | 0 | 2,663 | timm | 2022-12-13T07:06:15 | ---
tags:
- image-classification
- timm
library_tag: timm
license: apache-2.0
datasets:
- imagenet-1k
---
# Model card for convnext_atto_ols.a2_in1k
A ConvNeXt image classification model. Trained in `timm` on ImageNet-1k by Ross Wightman.
## Model Details
- **Model Type:** Image classification / feature backbone
- *... | 15,642 | [
[
-0.0670166015625,
-0.032501220703125,
-0.00386810302734375,
0.035919189453125,
-0.03216552734375,
-0.0156402587890625,
-0.01200103759765625,
-0.03485107421875,
0.0660400390625,
0.017669677734375,
-0.042877197265625,
-0.041717529296875,
-0.05133056640625,
-0.... |
internlm/internlm-chat-7b-v1_1 | 2023-10-20T14:23:08.000Z | [
"transformers",
"pytorch",
"internlm",
"text-generation",
"custom_code",
"region:us"
] | text-generation | internlm | null | null | internlm/internlm-chat-7b-v1_1 | 23 | 2,663 | transformers | 2023-08-21T14:24:51 | ---
pipeline_tag: text-generation
---
# InternLM
<div align="center">
<img src="https://github.com/InternLM/InternLM/assets/22529082/b9788105-8892-4398-8b47-b513a292378e" width="200"/>
<div> </div>
<div align="center">
<b><font size="5">InternLM</font></b>
<sup>
<a href="https://internlm.inter... | 10,351 | [
[
-0.0264892578125,
-0.054718017578125,
0.0027179718017578125,
0.03173828125,
-0.0144500732421875,
0.004150390625,
-0.012054443359375,
-0.0277862548828125,
-0.003353118896484375,
0.0010061264038085938,
-0.019439697265625,
-0.05242919921875,
-0.036102294921875,
... |
KappaNeuro/studio-ghibli-style | 2023-09-14T10:52:17.000Z | [
"diffusers",
"text-to-image",
"stable-diffusion",
"lora",
"studio ghibli",
"art",
"ghibli",
"style",
"painting",
"films",
"license:other",
"region:us",
"has_space"
] | text-to-image | KappaNeuro | null | null | KappaNeuro/studio-ghibli-style | 8 | 2,658 | diffusers | 2023-09-14T10:52:13 | ---
license: other
tags:
- text-to-image
- stable-diffusion
- lora
- diffusers
- studio ghibli
- art
- ghibli
- style
- painting
- films
base_model: stabilityai/stable-diffusion-xl-base-1.0
instance_prompt: Studio Ghibli Style
widget:
- text: "Studio Ghibli Style - Japanese soccer player Mina Tanaka overcomes crushing... | 6,440 | [
[
-0.039093017578125,
-0.03289794921875,
0.0223541259765625,
0.0264739990234375,
-0.015716552734375,
0.04547119140625,
-0.00457763671875,
-0.051544189453125,
0.061553955078125,
0.00838470458984375,
-0.08392333984375,
-0.02740478515625,
-0.032745361328125,
-0.0... |
Yntec/NovelAIRemix | 2023-09-24T08:54:37.000Z | [
"diffusers",
"Anime",
"text-to-image",
"license:creativeml-openrail-m",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | Yntec | null | null | Yntec/NovelAIRemix | 3 | 2,655 | diffusers | 2023-09-03T14:31:16 | ---
license: creativeml-openrail-m
library_name: diffusers
pipeline_tag: text-to-image
tags:
- Anime
---
# NovelAIRemix
NovelAI mixed with SD1.5.
Sample and prompt:
sitting elementary girl, Pret... | 1,078 | [
[
-0.035186767578125,
-0.03021240234375,
0.026123046875,
0.057769775390625,
-0.008026123046875,
-0.0023670196533203125,
0.0112762451171875,
-0.0295867919921875,
0.08367919921875,
0.042999267578125,
-0.05865478515625,
-0.034393310546875,
-0.043670654296875,
-0.... |
defog/sqlcoder-7b | 2023-10-04T13:46:35.000Z | [
"transformers",
"pytorch",
"mistral",
"text-generation",
"code",
"en",
"license:cc-by-sa-4.0",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | defog | null | null | defog/sqlcoder-7b | 30 | 2,653 | transformers | 2023-10-03T04:23:34 | ---
license: cc-by-sa-4.0
language:
- en
pipeline_tag: text-generation
tags:
- code
---
# Defog SQLCoder
Defog's SQLCoder is a state-of-the-art LLM for converting natural language questions to SQL queries.
[Interactive Demo](https://defog.ai/sqlcoder-demo/) | [🤗 HF Repo](https://huggingface.co/defog/sqlcoder2) | [♾️ ... | 4,364 | [
[
-0.0275421142578125,
-0.07379150390625,
0.0144500732421875,
0.0029754638671875,
-0.0187835693359375,
-0.019012451171875,
-0.007266998291015625,
-0.02557373046875,
0.005329132080078125,
0.039703369140625,
-0.0396728515625,
-0.04150390625,
-0.0284423828125,
0.... |
cryptoman/converted-llama-2-70b | 2023-07-21T15:43:53.000Z | [
"transformers",
"pytorch",
"llama",
"text-generation",
"facebook",
"meta",
"llama-2",
"en",
"arxiv:2307.09288",
"license:other",
"text-generation-inference",
"region:us"
] | text-generation | cryptoman | null | null | cryptoman/converted-llama-2-70b | 1 | 2,652 | transformers | 2023-07-20T08:49:12 | ---
inference: false
language:
- en
license: other
model_type: llama
pipeline_tag: text-generation
tags:
- facebook
- meta
- pytorch
- llama
- llama-2
---
# **Llama-2-70b converted to HF format**
These are the original weights of the LLaMA 70B models that have just been converted to Hugging Face Transformers format u... | 9,981 | [
[
-0.016326904296875,
-0.05126953125,
0.0266571044921875,
0.0161590576171875,
-0.027252197265625,
0.01580810546875,
-0.005588531494140625,
-0.0545654296875,
0.00782012939453125,
0.0232391357421875,
-0.05438232421875,
-0.04132080078125,
-0.051605224609375,
0.00... |
timm/vit_small_patch16_224.augreg_in21k | 2023-05-06T00:28:07.000Z | [
"timm",
"pytorch",
"safetensors",
"image-classification",
"dataset:imagenet-21k",
"arxiv:2106.10270",
"arxiv:2010.11929",
"license:apache-2.0",
"region:us"
] | image-classification | timm | null | null | timm/vit_small_patch16_224.augreg_in21k | 0 | 2,651 | timm | 2022-12-22T07:53:43 | ---
tags:
- image-classification
- timm
library_name: timm
license: apache-2.0
datasets:
- imagenet-21k
---
# Model card for vit_small_patch16_224.augreg_in21k
A Vision Transformer (ViT) image classification model. Trained on ImageNet-21k (with additional augmentation and regularization) in JAX by paper authors, porte... | 3,803 | [
[
-0.0396728515625,
-0.029693603515625,
-0.0011091232299804688,
0.0044708251953125,
-0.0265655517578125,
-0.0260009765625,
-0.024017333984375,
-0.036865234375,
0.01397705078125,
0.0223541259765625,
-0.0389404296875,
-0.03466796875,
-0.04638671875,
0.0020122528... |
facebook/muppet-roberta-base | 2021-06-28T21:44:23.000Z | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"exbert",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:2101.11038",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | fill-mask | facebook | null | null | facebook/muppet-roberta-base | 7 | 2,650 | transformers | 2022-03-02T23:29:05 | ---
language: en
tags:
- exbert
license: mit
datasets:
- bookcorpus
- wikipedia
---
# Muppet: Massive Multi-task Representations with Pre-Finetuning
# RoBERTa base model
This is a Massive Multi-task Pre-finetuned version of Roberta base. It was introduced in
[this paper](https://arxiv.org/abs/2101.11038). The model i... | 3,627 | [
[
-0.03131103515625,
-0.07159423828125,
0.01959228515625,
0.0106353759765625,
-0.00408172607421875,
-0.00331878662109375,
-0.036041259765625,
-0.031402587890625,
0.0167694091796875,
0.03271484375,
-0.048797607421875,
-0.022369384765625,
-0.054962158203125,
-0.... |
keremberke/yolov8s-pothole-segmentation | 2023-02-22T13:01:08.000Z | [
"ultralytics",
"tensorboard",
"v8",
"ultralyticsplus",
"yolov8",
"yolo",
"vision",
"image-segmentation",
"pytorch",
"awesome-yolov8-models",
"dataset:keremberke/pothole-segmentation",
"model-index",
"region:us"
] | image-segmentation | keremberke | null | null | keremberke/yolov8s-pothole-segmentation | 2 | 2,649 | ultralytics | 2023-01-26T03:12:06 |
---
tags:
- ultralyticsplus
- yolov8
- ultralytics
- yolo
- vision
- image-segmentation
- pytorch
- awesome-yolov8-models
library_name: ultralytics
library_version: 8.0.21
inference: false
datasets:
- keremberke/pothole-segmentation
model-index:
- name: keremberke/yolov8s-pothole-segmentation
results:
- task:
... | 1,986 | [
[
-0.033721923828125,
-0.03204345703125,
0.053619384765625,
-0.01157379150390625,
-0.038818359375,
-0.013519287109375,
0.01544952392578125,
-0.02862548828125,
0.0141754150390625,
0.0232696533203125,
-0.04180908203125,
-0.050811767578125,
-0.038055419921875,
-0... |
TheBloke/CodeLlama-7B-Instruct-GPTQ | 2023-09-27T12:46:05.000Z | [
"transformers",
"safetensors",
"llama",
"text-generation",
"llama-2",
"custom_code",
"code",
"arxiv:2308.12950",
"license:llama2",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | TheBloke | null | null | TheBloke/CodeLlama-7B-Instruct-GPTQ | 40 | 2,648 | transformers | 2023-08-24T20:27:24 | ---
language:
- code
license: llama2
tags:
- llama-2
model_name: CodeLlama 7B Instruct
base_model: codellama/CodeLlama-7b-instruct-hf
inference: false
model_creator: Meta
model_type: llama
pipeline_tag: text-generation
prompt_template: '[INST] Write code to solve the following coding problem that obeys
the constraint... | 21,148 | [
[
-0.0347900390625,
-0.0604248046875,
0.01168060302734375,
0.0092010498046875,
-0.02508544921875,
-0.009552001953125,
0.002094268798828125,
-0.035552978515625,
0.01224517822265625,
0.0279388427734375,
-0.043609619140625,
-0.04345703125,
-0.0244293212890625,
-0... |
keremberke/yolov8s-chest-xray-classification | 2023-02-22T13:02:05.000Z | [
"ultralytics",
"tensorboard",
"v8",
"ultralyticsplus",
"yolov8",
"yolo",
"vision",
"image-classification",
"pytorch",
"awesome-yolov8-models",
"dataset:keremberke/chest-xray-classification",
"model-index",
"region:us"
] | image-classification | keremberke | null | null | keremberke/yolov8s-chest-xray-classification | 0 | 2,647 | ultralytics | 2023-01-27T22:59:04 |
---
tags:
- ultralyticsplus
- yolov8
- ultralytics
- yolo
- vision
- image-classification
- pytorch
- awesome-yolov8-models
library_name: ultralytics
library_version: 8.0.21
inference: false
datasets:
- keremberke/chest-xray-classification
model-index:
- name: keremberke/yolov8s-chest-xray-classification
results:... | 1,796 | [
[
-0.02294921875,
-0.012542724609375,
0.042694091796875,
-0.022064208984375,
-0.03558349609375,
-0.02313232421875,
0.012298583984375,
-0.03045654296875,
0.01483917236328125,
0.02740478515625,
-0.0299530029296875,
-0.04833984375,
-0.046630859375,
-0.00640869140... |
kaiyuy/leandojo-lean3-tacgen-byt5-small | 2023-06-23T18:50:20.000Z | [
"transformers",
"pytorch",
"t5",
"text2text-generation",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text2text-generation | kaiyuy | null | null | kaiyuy/leandojo-lean3-tacgen-byt5-small | 1 | 2,647 | transformers | 2023-06-17T04:39:19 | ---
license: mit
inference:
parameters:
max_length: 1024
widget:
- text: "a b : ℕ\n⊢ a + b = b + a"
example_title: "Example"
---
[LeanDojo: Theorem Proving with Retrieval-Augmented Language Models](https://arxiv.org/abs/xxxx.xxxxx)
Under review, NeurIPS (Datasets and Benchmarks Track), 2023
[Kaiyu Yang... | 1,223 | [
[
-0.0186767578125,
-0.017913818359375,
0.04193115234375,
0.018463134765625,
0.0052947998046875,
-0.00983428955078125,
-0.0233001708984375,
-0.037933349609375,
0.01441192626953125,
0.026580810546875,
-0.00701141357421875,
-0.047332763671875,
-0.048065185546875,
... |
artificialguybr/analogredmond | 2023-10-07T06:25:45.000Z | [
"diffusers",
"text-to-image",
"stable-diffusion",
"lora",
"license:creativeml-openrail-m",
"has_space",
"region:us"
] | text-to-image | artificialguybr | null | null | artificialguybr/analogredmond | 4 | 2,645 | diffusers | 2023-08-17T01:21:20 | ---
license: creativeml-openrail-m
tags:
- text-to-image
- stable-diffusion
- lora
- diffusers
base_model: stabilityai/stable-diffusion-xl-base-1.0
instance_prompt: AnalogRedmAF
widget:
- text: AnalogRedmAF
---
# Analog.Redmond
Analog.Redmond is here!
V2 HERE:https://huggingface.co/a... | 1,360 | [
[
-0.05841064453125,
-0.0689697265625,
0.0245513916015625,
0.0093536376953125,
-0.038848876953125,
0.0003867149353027344,
0.0279388427734375,
-0.0638427734375,
0.086669921875,
0.018310546875,
-0.055206298828125,
-0.0259552001953125,
-0.014801025390625,
-0.0129... |
Yntec/RainbowDreams | 2023-07-12T12:33:08.000Z | [
"diffusers",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"yntec",
"dreamlike",
"rainbowpatch",
"license:creativeml-openrail-m",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | Yntec | null | null | Yntec/RainbowDreams | 1 | 2,644 | diffusers | 2023-07-11T16:20:50 | ---
license: creativeml-openrail-m
library_name: diffusers
pipeline_tag: text-to-image
tags:
- stable-diffusion
- stable-diffusion-diffusers
- diffusers
- text-to-image
- yntec
- dreamlike
- rainbowpatch
- diffusers
---
# RainbowDreams
A mix of Rainbowpatch 1.0 by Patchmonk at https://civitai.com/models/5528/rainbowp... | 422 | [
[
-0.06439208984375,
-0.0244293212890625,
-0.002758026123046875,
0.09600830078125,
-0.0266571044921875,
0.00067138671875,
0.0445556640625,
-0.047698974609375,
0.06488037109375,
0.0516357421875,
-0.0926513671875,
-0.00579071044921875,
-0.021759033203125,
-0.016... |
keremberke/yolov8n-csgo-player-detection | 2023-02-22T13:02:39.000Z | [
"ultralytics",
"tensorboard",
"v8",
"ultralyticsplus",
"yolov8",
"yolo",
"vision",
"object-detection",
"pytorch",
"awesome-yolov8-models",
"dataset:keremberke/csgo-object-detection",
"model-index",
"region:us"
] | object-detection | keremberke | null | null | keremberke/yolov8n-csgo-player-detection | 7 | 2,643 | ultralytics | 2023-01-29T01:17:24 |
---
tags:
- ultralyticsplus
- yolov8
- ultralytics
- yolo
- vision
- object-detection
- pytorch
- awesome-yolov8-models
library_name: ultralytics
library_version: 8.0.21
inference: false
datasets:
- keremberke/csgo-object-detection
model-index:
- name: keremberke/yolov8n-csgo-player-detection
results:
- task:
... | 1,835 | [
[
-0.03515625,
-0.028717041015625,
0.0367431640625,
-0.018157958984375,
-0.024871826171875,
-0.002857208251953125,
-0.003154754638671875,
-0.03662109375,
0.020782470703125,
0.0098876953125,
-0.047882080078125,
-0.044097900390625,
-0.031951904296875,
-0.0145568... |
facebook/timesformer-base-finetuned-ssv2 | 2022-12-12T12:53:06.000Z | [
"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-ssv2 | 2 | 2,642 | transformers | 2022-10-07T20:36:48 | ---
license: "cc-by-nc-4.0"
tags:
- vision
- video-classification
---
# TimeSformer (base-sized model, fine-tuned on Something Something v2)
TimeSformer model pre-trained on [Something Something v2](https://developer.qualcomm.com/software/ai-datasets/something-something). It was introduced in the paper [TimeSformer:... | 1,989 | [
[
-0.0181121826171875,
-0.05224609375,
0.015594482421875,
0.01235198974609375,
-0.01302337646484375,
-0.000010848045349121094,
0.001941680908203125,
-0.0121612548828125,
-0.005584716796875,
-0.0025348663330078125,
-0.056121826171875,
-0.0194244384765625,
-0.062133... |
openai/shap-e | 2023-07-20T16:02:25.000Z | [
"diffusers",
"text-to-image",
"text-to-3d",
"shap-e",
"arxiv:2305.02463",
"license:mit",
"has_space",
"diffusers:ShapEPipeline",
"region:us"
] | text-to-image | openai | null | null | openai/shap-e | 27 | 2,642 | diffusers | 2023-07-04T13:25:35 | ---
license: mit
tags:
- text-to-image
- text-to-3d
- shap-e
- diffusers
---
# Shap-E
Shap-E introduces a diffusion process that can generate a 3D image from a text prompt. It was introduced in [Shap-E: Generating Conditional 3D Implicit Functions](https://arxiv.org/abs/2305.02463) by Heewoo Jun and Alex Nichol from ... | 3,884 | [
[
-0.039794921875,
-0.06658935546875,
0.044921875,
0.01334381103515625,
-0.01268768310546875,
-0.035400390625,
0.01316070556640625,
-0.047149658203125,
0.018768310546875,
0.0168914794921875,
-0.036224365234375,
-0.0304718017578125,
-0.0447998046875,
0.00175762... |
keremberke/yolov8n-hard-hat-detection | 2023-02-22T13:04:34.000Z | [
"ultralytics",
"tensorboard",
"v8",
"ultralyticsplus",
"yolov8",
"yolo",
"vision",
"object-detection",
"pytorch",
"awesome-yolov8-models",
"dataset:keremberke/hard-hat-detection",
"model-index",
"region:us"
] | object-detection | keremberke | null | null | keremberke/yolov8n-hard-hat-detection | 1 | 2,640 | ultralytics | 2023-01-29T22:41:13 |
---
tags:
- ultralyticsplus
- yolov8
- ultralytics
- yolo
- vision
- object-detection
- pytorch
- awesome-yolov8-models
library_name: ultralytics
library_version: 8.0.23
inference: false
datasets:
- keremberke/hard-hat-detection
model-index:
- name: keremberke/yolov8n-hard-hat-detection
results:
- task:
t... | 1,809 | [
[
-0.034942626953125,
-0.027252197265625,
0.040374755859375,
-0.0186920166015625,
-0.0292205810546875,
-0.0106201171875,
-0.00586700439453125,
-0.034912109375,
0.023040771484375,
0.0174560546875,
-0.055145263671875,
-0.05487060546875,
-0.0295562744140625,
-0.0... |
nvidia/mit-b4 | 2022-08-06T10:28:21.000Z | [
"transformers",
"pytorch",
"tf",
"segformer",
"image-classification",
"vision",
"dataset:imagenet_1k",
"arxiv:2105.15203",
"license:other",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | image-classification | nvidia | null | null | nvidia/mit-b4 | 1 | 2,639 | transformers | 2022-03-02T23:29:05 | ---
license: other
tags:
- vision
datasets:
- imagenet_1k
widget:
- src: https://huggingface.co/datasets/hf-internal-testing/fixtures_ade20k/resolve/main/ADE_val_00000001.jpg
example_title: House
- src: https://huggingface.co/datasets/hf-internal-testing/fixtures_ade20k/resolve/main/ADE_val_00000002.jpg
example_tit... | 3,354 | [
[
-0.06866455078125,
-0.051025390625,
0.006443023681640625,
0.01100921630859375,
-0.0247344970703125,
-0.0259246826171875,
0.003246307373046875,
-0.04815673828125,
0.01885986328125,
0.043609619140625,
-0.060546875,
-0.03985595703125,
-0.057220458984375,
0.0091... |
sadakmed/distiluse-base-multilingual-cased-v2 | 2021-09-22T09:37:21.000Z | [
"sentence-transformers",
"pytorch",
"distilbert",
"DistilBert",
"Universal Sentence Encoder",
"sentence-embeddings",
"sentence-similarity",
"multilingual",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | sentence-similarity | sadakmed | null | null | sadakmed/distiluse-base-multilingual-cased-v2 | 1 | 2,636 | sentence-transformers | 2022-03-02T23:29:05 | ---
language: multilingual
tags:
- DistilBert
- Universal Sentence Encoder
- sentence-embeddings
- sentence-transformers
- sentence-similarity
license: apache-2.0
---
While v1 model supports 15 languages, this version supports 50+ languages. However, performance on the 15 languages mentioned in v1 are reported to be a... | 441 | [
[
-0.030426025390625,
-0.0567626953125,
0.024444580078125,
0.03765869140625,
-0.0275115966796875,
0.00035881996154785156,
-0.00328826904296875,
-0.067138671875,
-0.01129150390625,
0.053924560546875,
-0.052734375,
-0.0257568359375,
-0.021392822265625,
0.0089874... |
keremberke/yolov8n-forklift-detection | 2023-02-22T13:00:05.000Z | [
"ultralytics",
"tensorboard",
"v8",
"ultralyticsplus",
"yolov8",
"yolo",
"vision",
"object-detection",
"pytorch",
"awesome-yolov8-models",
"dataset:keremberke/forklift-object-detection",
"model-index",
"region:us"
] | object-detection | keremberke | null | null | keremberke/yolov8n-forklift-detection | 2 | 2,636 | ultralytics | 2023-01-15T15:49:05 |
---
tags:
- ultralyticsplus
- yolov8
- ultralytics
- yolo
- vision
- object-detection
- pytorch
- awesome-yolov8-models
library_name: ultralytics
library_version: 8.0.21
inference: false
datasets:
- keremberke/forklift-object-detection
model-index:
- name: keremberke/yolov8n-forklift-detection
results:
- task:
... | 1,827 | [
[
-0.034332275390625,
-0.01611328125,
0.03564453125,
-0.0284576416015625,
-0.030426025390625,
-0.0237274169921875,
0.02044677734375,
-0.0379638671875,
0.0244598388671875,
0.013702392578125,
-0.04937744140625,
-0.043060302734375,
-0.030242919921875,
-0.00152206... |
Yntec/Dreamlike | 2023-09-14T05:07:37.000Z | [
"diffusers",
"photorealistic",
"photoreal",
"art",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"en",
"license:other",
"has_space",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | Yntec | null | null | Yntec/Dreamlike | 1 | 2,635 | diffusers | 2023-08-23T23:52:12 | ---
license: other
library_name: diffusers
pipeline_tag: text-to-image
tags:
- photorealistic
- photoreal
- art
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
language:
- en
inference: false
---
# Dreamlike
What happens when in the process of making your mix you have to create an intermed... | 1,295 | [
[
-0.04168701171875,
-0.05657958984375,
0.0460205078125,
0.020782470703125,
-0.0243377685546875,
0.0286712646484375,
0.009246826171875,
-0.05657958984375,
0.0826416015625,
0.06134033203125,
-0.0770263671875,
-0.01090240478515625,
-0.032470703125,
-0.0067367553... |
SaiCharan7829/my-pet-dog | 2023-10-07T07:17:24.000Z | [
"diffusers",
"NxtWave-GenAI-Webinar",
"text-to-image",
"stable-diffusion",
"license:creativeml-openrail-m",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | SaiCharan7829 | null | null | SaiCharan7829/my-pet-dog | 0 | 2,634 | diffusers | 2023-10-07T07:13:20 | ---
license: creativeml-openrail-m
tags:
- NxtWave-GenAI-Webinar
- text-to-image
- stable-diffusion
---
### My-Pet-Dog Dreambooth model trained by SaiCharan7829 following the "Build your own Gen AI model" session by NxtWave.
Project Submission Code: GoX19932gAS
Sample pictures of this concept:
![0](https://hugging... | 406 | [
[
-0.059478759765625,
-0.01605224609375,
0.0297393798828125,
0.01004791259765625,
-0.0099639892578125,
0.03131103515625,
0.0269775390625,
-0.0310516357421875,
0.045196533203125,
0.02838134765625,
-0.03985595703125,
-0.0173492431640625,
-0.01393890380859375,
0.... |
keremberke/yolov8n-nlf-head-detection | 2023-02-22T13:04:55.000Z | [
"ultralytics",
"tensorboard",
"v8",
"ultralyticsplus",
"yolov8",
"yolo",
"vision",
"object-detection",
"pytorch",
"awesome-yolov8-models",
"dataset:keremberke/nfl-object-detection",
"model-index",
"region:us"
] | object-detection | keremberke | null | null | keremberke/yolov8n-nlf-head-detection | 1 | 2,632 | ultralytics | 2023-01-30T06:27:18 |
---
tags:
- ultralyticsplus
- yolov8
- ultralytics
- yolo
- vision
- object-detection
- pytorch
- awesome-yolov8-models
library_name: ultralytics
library_version: 8.0.23
inference: false
datasets:
- keremberke/nfl-object-detection
model-index:
- name: keremberke/yolov8n-nlf-head-detection
results:
- task:
... | 1,875 | [
[
-0.04119873046875,
-0.029632568359375,
0.03521728515625,
-0.0112152099609375,
-0.029296875,
-0.01171112060546875,
0.005947113037109375,
-0.042022705078125,
0.02935791015625,
0.01849365234375,
-0.059417724609375,
-0.052520751953125,
-0.0338134765625,
-0.00006... |
sebastian-hofstaetter/distilbert-dot-tas_b-b256-msmarco | 2021-04-15T08:54:28.000Z | [
"transformers",
"pytorch",
"distilbert",
"feature-extraction",
"dpr",
"dense-passage-retrieval",
"knowledge-distillation",
"en",
"dataset:ms_marco",
"arxiv:2104.06967",
"endpoints_compatible",
"has_space",
"region:us"
] | feature-extraction | sebastian-hofstaetter | null | null | sebastian-hofstaetter/distilbert-dot-tas_b-b256-msmarco | 20 | 2,631 | transformers | 2022-03-02T23:29:05 | ---
language: "en"
tags:
- dpr
- dense-passage-retrieval
- knowledge-distillation
datasets:
- ms_marco
---
# DistilBert for Dense Passage Retrieval trained with Balanced Topic Aware Sampling (TAS-B)
We provide a retrieval trained DistilBert-based model (we call the *dual-encoder then dot-product scoring* ... | 3,746 | [
[
-0.039825439453125,
-0.0703125,
0.029510498046875,
0.02008056640625,
-0.026153564453125,
-0.00910186767578125,
-0.01251220703125,
-0.0195465087890625,
0.0210723876953125,
0.021484375,
-0.006591796875,
-0.044921875,
-0.0509033203125,
-0.003936767578125,
-... |
keremberke/yolov8n-protective-equipment-detection | 2023-02-22T13:03:41.000Z | [
"ultralytics",
"tensorboard",
"v8",
"ultralyticsplus",
"yolov8",
"yolo",
"vision",
"object-detection",
"pytorch",
"awesome-yolov8-models",
"dataset:keremberke/protective-equipment-detection",
"model-index",
"region:us"
] | object-detection | keremberke | null | null | keremberke/yolov8n-protective-equipment-detection | 0 | 2,629 | ultralytics | 2023-01-29T09:47:40 |
---
tags:
- ultralyticsplus
- yolov8
- ultralytics
- yolo
- vision
- object-detection
- pytorch
- awesome-yolov8-models
library_name: ultralytics
library_version: 8.0.21
inference: false
datasets:
- keremberke/protective-equipment-detection
model-index:
- name: keremberke/yolov8n-protective-equipment-detection
re... | 1,977 | [
[
-0.0293121337890625,
-0.0201873779296875,
0.0328369140625,
-0.028839111328125,
-0.033172607421875,
-0.01422882080078125,
0.0161590576171875,
-0.03631591796875,
0.0196990966796875,
0.017303466796875,
-0.04949951171875,
-0.053680419921875,
-0.028076171875,
-0.... |
HooshvareLab/bert-fa-zwnj-base | 2021-05-18T21:05:42.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"fa",
"arxiv:2005.12515",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us",
"has_space"
] | fill-mask | HooshvareLab | null | null | HooshvareLab/bert-fa-zwnj-base | 6 | 2,626 | transformers | 2022-03-02T23:29:04 | ---
language: fa
license: apache-2.0
---
# ParsBERT (v3.0)
A Transformer-based Model for Persian Language Understanding
The new version of BERT v3.0 for Persian is available today and can tackle the zero-width non-joiner character for Persian writing. Also, the model was trained on new multi-types corpora with a new ... | 1,124 | [
[
-0.02117919921875,
-0.0596923828125,
0.036102294921875,
0.0199737548828125,
-0.027130126953125,
0.00888824462890625,
-0.033447265625,
-0.0249176025390625,
0.017333984375,
0.044647216796875,
-0.036407470703125,
-0.03143310546875,
-0.023345947265625,
-0.005237... |
KM4STfulltext/SSCI-BERT-e2 | 2022-12-24T03:20:32.000Z | [
"transformers",
"pytorch",
"bert",
"fill-mask",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | fill-mask | KM4STfulltext | null | null | KM4STfulltext/SSCI-BERT-e2 | 1 | 2,626 | transformers | 2022-06-01T08:59:09 | ---
license: apache-2.0
---
# SSCI-BERT: A pretrained language model for social scientific text
## Introduction
The research for social science texts needs the support natural language processing tools.
The pre-trained language model has greatly improved the accuracy of text mining in general texts. At present, th... | 9,021 | [
[
-0.0228271484375,
-0.0209197998046875,
0.016998291015625,
0.010406494140625,
-0.0165863037109375,
0.0032558441162109375,
-0.00632476806640625,
-0.0223388671875,
0.03570556640625,
0.005626678466796875,
-0.034637451171875,
-0.05450439453125,
-0.062164306640625,
... |
keremberke/yolov8n-blood-cell-detection | 2023-02-22T13:03:12.000Z | [
"ultralytics",
"tensorboard",
"v8",
"ultralyticsplus",
"yolov8",
"yolo",
"vision",
"object-detection",
"pytorch",
"awesome-yolov8-models",
"dataset:keremberke/blood-cell-object-detection",
"model-index",
"region:us"
] | object-detection | keremberke | null | null | keremberke/yolov8n-blood-cell-detection | 2 | 2,624 | ultralytics | 2023-01-29T05:06:49 |
---
tags:
- ultralyticsplus
- yolov8
- ultralytics
- yolo
- vision
- object-detection
- pytorch
- awesome-yolov8-models
library_name: ultralytics
library_version: 8.0.21
inference: false
datasets:
- keremberke/blood-cell-object-detection
model-index:
- name: keremberke/yolov8n-blood-cell-detection
results:
- ta... | 1,846 | [
[
-0.0299530029296875,
-0.0185089111328125,
0.03387451171875,
-0.026458740234375,
-0.041595458984375,
-0.005939483642578125,
0.02337646484375,
-0.037322998046875,
0.031280517578125,
0.02154541015625,
-0.038604736328125,
-0.048828125,
-0.0234222412109375,
0.003... |
keremberke/yolov8n-scene-classification | 2023-02-22T13:00:14.000Z | [
"ultralytics",
"tensorboard",
"v8",
"ultralyticsplus",
"yolov8",
"yolo",
"vision",
"image-classification",
"pytorch",
"awesome-yolov8-models",
"dataset:keremberke/indoor-scene-classification",
"model-index",
"region:us"
] | image-classification | keremberke | null | null | keremberke/yolov8n-scene-classification | 1 | 2,623 | ultralytics | 2023-01-27T01:35:34 |
---
tags:
- ultralyticsplus
- yolov8
- ultralytics
- yolo
- vision
- image-classification
- pytorch
- awesome-yolov8-models
library_name: ultralytics
library_version: 8.0.20
inference: false
datasets:
- keremberke/indoor-scene-classification
model-index:
- name: keremberke/yolov8n-scene-classification
results:
... | 2,613 | [
[
-0.03521728515625,
-0.0281829833984375,
0.0272064208984375,
-0.0226593017578125,
-0.0062103271484375,
-0.007099151611328125,
0.01317596435546875,
-0.027099609375,
0.01202392578125,
0.0301666259765625,
-0.04254150390625,
-0.052947998046875,
-0.034881591796875,
... |
biu-nlp/abstract-sim-sentence | 2023-05-26T08:20:51.000Z | [
"transformers",
"pytorch",
"mpnet",
"fill-mask",
"feature-extraction",
"sentence-similarity",
"en",
"dataset:biu-nlp/abstract-sim",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | feature-extraction | biu-nlp | null | null | biu-nlp/abstract-sim-sentence | 15 | 2,623 | transformers | 2023-05-13T14:06:28 | ---
language:
- en
tags:
- feature-extraction
- sentence-similarity
datasets:
- biu-nlp/abstract-sim
widgets:
- sentence-similarity
- feature-extraction
---
A model for mapping abstract sentence descriptions to sentences that fit the descriptions. Trained on Wikipedia. Use ```load_finetuned_model``` to load the query ... | 4,981 | [
[
-0.013214111328125,
-0.042510986328125,
0.0283966064453125,
0.0142974853515625,
-0.0186767578125,
-0.007965087890625,
-0.01081085205078125,
-0.0146636962890625,
0.0279998779296875,
0.036376953125,
-0.053009033203125,
-0.0313720703125,
-0.0234375,
0.011306762... |
Yntec/ArcticFowl | 2023-08-10T22:59:14.000Z | [
"diffusers",
"anime",
"art",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"ArcticFlamingo",
"en",
"license:creativeml-openrail-m",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | Yntec | null | null | Yntec/ArcticFowl | 3 | 2,621 | diffusers | 2023-08-09T20:38:20 | ---
license: creativeml-openrail-m
language:
- en
library_name: diffusers
pipeline_tag: text-to-image
tags:
- anime
- art
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
- ArcticFlamingo
---
This model with the Blessed2 VAE baked in.
Demo image by digiplay:
![demo](https://cdn-uploads.hug... | 932 | [
[
-0.007297515869140625,
-0.049713134765625,
0.0283050537109375,
0.018157958984375,
-0.0259857177734375,
-0.005565643310546875,
0.031402587890625,
-0.0318603515625,
0.03594970703125,
0.0562744140625,
-0.032928466796875,
-0.016937255859375,
-0.045989990234375,
... |
keremberke/yolov8s-blood-cell-detection | 2023-02-22T13:03:07.000Z | [
"ultralytics",
"tensorboard",
"v8",
"ultralyticsplus",
"yolov8",
"yolo",
"vision",
"object-detection",
"pytorch",
"awesome-yolov8-models",
"dataset:keremberke/blood-cell-object-detection",
"model-index",
"region:us"
] | object-detection | keremberke | null | null | keremberke/yolov8s-blood-cell-detection | 1 | 2,616 | ultralytics | 2023-01-29T05:24:20 |
---
tags:
- ultralyticsplus
- yolov8
- ultralytics
- yolo
- vision
- object-detection
- pytorch
- awesome-yolov8-models
library_name: ultralytics
library_version: 8.0.21
inference: false
datasets:
- keremberke/blood-cell-object-detection
model-index:
- name: keremberke/yolov8s-blood-cell-detection
results:
- ta... | 1,846 | [
[
-0.0298309326171875,
-0.0167083740234375,
0.03619384765625,
-0.026031494140625,
-0.041229248046875,
-0.00472259521484375,
0.024078369140625,
-0.03680419921875,
0.030364990234375,
0.0214996337890625,
-0.037567138671875,
-0.049224853515625,
-0.0227813720703125,
... |
KoboldAI/GPT-Neo-2.7B-Janeway | 2022-03-20T12:57:50.000Z | [
"transformers",
"pytorch",
"gpt_neo",
"text-generation",
"en",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-generation | KoboldAI | null | null | KoboldAI/GPT-Neo-2.7B-Janeway | 6 | 2,614 | transformers | 2022-03-02T23:29:04 | ---
language: en
license: mit
---
# GPT-Neo 2.7B - Janeway
## Model Description
GPT-Neo 2.7B-Janeway is a finetune created using EleutherAI's GPT-Neo 2.7B model.
## Training data
The training data contains around 2210 ebooks, mostly in the sci-fi and fantasy genres. The dataset is based on the same dataset used... | 2,681 | [
[
-0.0135955810546875,
-0.056915283203125,
0.0301666259765625,
0.00016009807586669922,
-0.02081298828125,
-0.018829345703125,
-0.005580902099609375,
-0.0243682861328125,
0.0017023086547851562,
0.043304443359375,
-0.04046630859375,
-0.033660888671875,
-0.0532531738... |
Yntec/AgarthaChadstyle | 2023-11-04T03:31:27.000Z | [
"diffusers",
"Style",
"Abstract",
"Surrealism",
"ChadUltraF3",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"license:creativeml-openrail-m",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"region:us",
"has_space"
] | text-to-image | Yntec | null | null | Yntec/AgarthaChadstyle | 0 | 2,611 | diffusers | 2023-11-04T02:50:41 | ---
license: creativeml-openrail-m
library_name: diffusers
pipeline_tag: text-to-image
tags:
- Style
- Abstract
- Surrealism
- ChadUltraF3
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
---
# 🌈🧬🍭🍄👁️ Agartha 👁️🍄🍭🧬🌈(ChadStyle)
Check the many trigger words of this m... | 781 | [
[
-0.033935546875,
-0.07586669921875,
0.00453948974609375,
0.0288848876953125,
-0.027374267578125,
0.003238677978515625,
0.0101165771484375,
-0.039215087890625,
0.0728759765625,
0.01091766357421875,
-0.058929443359375,
-0.0303192138671875,
-0.05743408203125,
-... |
Twitter/twhin-bert-base | 2023-07-07T03:38:25.000Z | [
"transformers",
"pytorch",
"safetensors",
"bert",
"fill-mask",
"Twitter",
"Multilingual",
"en",
"ja",
"pt",
"es",
"ko",
"ar",
"tr",
"th",
"fr",
"id",
"ru",
"de",
"fa",
"it",
"zh",
"pl",
"hi",
"ur",
"nl",
"el",
"ms",
"ca",
"sr",
"sv",
"uk",
"he",
"fi"... | fill-mask | Twitter | null | null | Twitter/twhin-bert-base | 25 | 2,609 | transformers | 2022-10-18T18:34:23 | ---
language:
- en
- ja
- pt
- es
- ko
- ar
- tr
- th
- fr
- id
- ru
- de
- fa
- it
- zh
- pl
- hi
- ur
- nl
- el
- ms
- ca
- sr
- sv
- uk
- he
- fi
- cs
- ta
- ne
- vi
- hu
- eo
- bn
- mr
- ml
- hr
- no
- sw
- sl
- te
- az
- da
- ... | 3,440 | [
[
-0.016021728515625,
-0.046905517578125,
0.0109710693359375,
0.0406494140625,
-0.01715087890625,
0.01256561279296875,
-0.051849365234375,
-0.049530029296875,
0.03692626953125,
0.004852294921875,
-0.042938232421875,
-0.036651611328125,
-0.054351806640625,
-0.0... |
gustavorayo/ryo-takemasa-v1 | 2023-10-22T11:48:39.000Z | [
"diffusers",
"text-to-image",
"stable-diffusion",
"license:creativeml-openrail-m",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | gustavorayo | null | null | gustavorayo/ryo-takemasa-v1 | 0 | 2,609 | diffusers | 2023-10-22T11:44:36 | ---
license: creativeml-openrail-m
tags:
- text-to-image
- stable-diffusion
---
### ryo-takemasa-v1 Dreambooth model trained by gustavorayo with [TheLastBen's fast-DreamBooth](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast-DreamBooth.ipynb) notebook
Test the concept via A1111... | 508 | [
[
-0.023284912109375,
-0.047637939453125,
0.049896240234375,
0.0243988037109375,
-0.0275421142578125,
0.0208740234375,
0.0246734619140625,
-0.033966064453125,
0.058929443359375,
0.00835418701171875,
-0.02880859375,
-0.023040771484375,
-0.044769287109375,
-0.01... |
Unbabel/gec-t5_small | 2021-09-27T11:27:48.000Z | [
"transformers",
"pytorch",
"t5",
"text2text-generation",
"grammatical error correction",
"text2text",
"en",
"dataset:clang-8",
"dataset:conll-14",
"dataset:conll-13",
"arxiv:2106.03830",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"text-generation... | text2text-generation | Unbabel | null | null | Unbabel/gec-t5_small | 15 | 2,607 | transformers | 2022-03-02T23:29:05 | ---
language:
- en
tags:
- grammatical error correction
- text2text
- t5
license: apache-2.0
datasets:
- clang-8
- conll-14
- conll-13
metrics:
- f0.5
---
This model is an implementation of the paper [A Simple Recipe for Multilingual Grammatical Error Correction](https://arxiv.org/pdf/2106.03830.pdf) from Google where... | 1,387 | [
[
-0.01171875,
-0.046142578125,
0.0447998046875,
0.0212554931640625,
-0.01288604736328125,
-0.0158233642578125,
-0.02838134765625,
-0.0228271484375,
0.005992889404296875,
0.004550933837890625,
-0.061614990234375,
-0.06427001953125,
-0.04547119140625,
0.0299224... |
snunlp/KR-FinBert-SC | 2022-04-28T05:07:18.000Z | [
"transformers",
"pytorch",
"bert",
"text-classification",
"ko",
"endpoints_compatible",
"has_space",
"region:us"
] | text-classification | snunlp | null | null | snunlp/KR-FinBert-SC | 12 | 2,606 | transformers | 2022-03-02T23:29:05 | ---
language:
- ko
---
# KR-FinBert & KR-FinBert-SC
Much progress has been made in the NLP (Natural Language Processing) field, with numerous studies showing that domain adaptation using small-scale corpus and fine-tuning with labeled data is effective for overall performance improvement.
we proposed KR-FinBert for... | 2,669 | [
[
-0.039215087890625,
-0.041351318359375,
0.01323699951171875,
0.03118896484375,
-0.027435302734375,
0.004852294921875,
-0.021331787109375,
-0.0284271240234375,
0.0195465087890625,
0.03253173828125,
-0.03570556640625,
-0.052276611328125,
-0.054656982421875,
-0... |
google/vit-hybrid-base-bit-384 | 2023-09-11T20:45:52.000Z | [
"transformers",
"pytorch",
"safetensors",
"vit-hybrid",
"image-classification",
"vision",
"dataset:imagenet-1k",
"arxiv:2010.11929",
"arxiv:2006.03677",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | image-classification | google | null | null | google/vit-hybrid-base-bit-384 | 4 | 2,603 | transformers | 2022-12-06T17:38:55 | ---
license: apache-2.0
tags:
- vision
- image-classification
datasets:
- imagenet-1k
---
# Vision Transformer (base-sized model) - Hybrid
The hybrid Vision Transformer (ViT) model was proposed in [An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale](https://arxiv.org/abs/2010.11929) by Alexey ... | 5,212 | [
[
-0.048675537109375,
-0.02032470703125,
-0.0104217529296875,
-0.005214691162109375,
-0.0253753662109375,
-0.0104827880859375,
-0.018218994140625,
-0.05340576171875,
0.00981903076171875,
0.0277252197265625,
-0.01873779296875,
-0.01947021484375,
-0.050262451171875,... |
keremberke/yolov8n-pokemon-classification | 2023-02-22T13:01:59.000Z | [
"ultralytics",
"tensorboard",
"v8",
"ultralyticsplus",
"yolov8",
"yolo",
"vision",
"image-classification",
"pytorch",
"awesome-yolov8-models",
"dataset:keremberke/pokemon-classification",
"model-index",
"region:us"
] | image-classification | keremberke | null | null | keremberke/yolov8n-pokemon-classification | 1 | 2,603 | ultralytics | 2023-01-28T04:03:32 |
---
tags:
- ultralyticsplus
- yolov8
- ultralytics
- yolo
- vision
- image-classification
- pytorch
- awesome-yolov8-models
library_name: ultralytics
library_version: 8.0.21
inference: false
datasets:
- keremberke/pokemon-classification
model-index:
- name: keremberke/yolov8n-pokemon-classification
results:
- t... | 3,001 | [
[
-0.040069580078125,
-0.0136260986328125,
0.0178375244140625,
-0.0062103271484375,
-0.00957489013671875,
0.0120086669921875,
0.01226043701171875,
-0.02166748046875,
0.0413818359375,
0.017486572265625,
-0.0275115966796875,
-0.03778076171875,
-0.04766845703125,
... |
keremberke/yolov8s-nlf-head-detection | 2023-02-22T13:04:29.000Z | [
"ultralytics",
"tensorboard",
"v8",
"ultralyticsplus",
"yolov8",
"yolo",
"vision",
"object-detection",
"pytorch",
"awesome-yolov8-models",
"dataset:keremberke/nfl-object-detection",
"model-index",
"region:us"
] | object-detection | keremberke | null | null | keremberke/yolov8s-nlf-head-detection | 1 | 2,602 | ultralytics | 2023-01-29T19:46:30 |
---
tags:
- ultralyticsplus
- yolov8
- ultralytics
- yolo
- vision
- object-detection
- pytorch
- awesome-yolov8-models
library_name: ultralytics
library_version: 8.0.23
inference: false
datasets:
- keremberke/nfl-object-detection
model-index:
- name: keremberke/yolov8s-nlf-head-detection
results:
- task:
... | 1,875 | [
[
-0.04095458984375,
-0.02801513671875,
0.036346435546875,
-0.01213836669921875,
-0.029510498046875,
-0.01116943359375,
0.006137847900390625,
-0.041534423828125,
0.02899169921875,
0.0184326171875,
-0.058624267578125,
-0.052764892578125,
-0.03460693359375,
0.00... |
facebook/timesformer-hr-finetuned-k600 | 2022-12-12T12:53:13.000Z | [
"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-hr-finetuned-k600 | 2 | 2,601 | transformers | 2022-10-07T22:51:20 | ---
license: "cc-by-nc-4.0"
tags:
- vision
- video-classification
---
# TimeSformer (base-sized model, fine-tuned on Kinetics-600)
TimeSformer model pre-trained on [Kinetics-600](https://www.deepmind.com/open-source/kinetics). It was introduced in the paper [TimeSformer: Is Space-Time Attention All You Need for Vide... | 1,930 | [
[
-0.0169830322265625,
-0.042510986328125,
0.024932861328125,
0.006549835205078125,
-0.0112762451171875,
0.005046844482421875,
0.000507354736328125,
-0.004428863525390625,
-0.0005860328674316406,
-0.00879669189453125,
-0.05621337890625,
-0.026885986328125,
-0.0601... |
livingbox/incremental-test-03 | 2023-10-30T20:42:29.000Z | [
"diffusers",
"text-to-image",
"stable-diffusion",
"license:creativeml-openrail-m",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"region:us",
"has_space"
] | text-to-image | livingbox | null | null | livingbox/incremental-test-03 | 0 | 2,600 | diffusers | 2023-10-30T20:37:18 | ---
license: creativeml-openrail-m
tags:
- text-to-image
- stable-diffusion
---
### Incremental-test-03 Dreambooth model trained by livingbox with [TheLastBen's fast-DreamBooth](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast-DreamBooth.ipynb) notebook
Test the concept via A11... | 510 | [
[
-0.03106689453125,
-0.08160400390625,
0.032623291015625,
0.05224609375,
-0.01334381103515625,
0.03759765625,
0.028076171875,
-0.0264129638671875,
0.038421630859375,
0.0045928955078125,
-0.032257080078125,
-0.0146636962890625,
-0.0237274169921875,
-0.00361251... |
microsoft/resnet-34 | 2023-06-26T19:49:23.000Z | [
"transformers",
"pytorch",
"tf",
"safetensors",
"resnet",
"image-classification",
"vision",
"dataset:imagenet-1k",
"arxiv:1512.03385",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | image-classification | microsoft | null | null | microsoft/resnet-34 | 4 | 2,598 | transformers | 2022-03-16T15:41:51 | ---
license: apache-2.0
tags:
- vision
- image-classification
datasets:
- imagenet-1k
---
# ResNet-34 v1.5
ResNet model pre-trained on ImageNet-1k at resolution 224x224. It was introduced in the paper [Deep Residual Learning for Image Recognition](https://arxiv.org/abs/1512.03385) by He et al.
Disclaimer: The team ... | 2,662 | [
[
-0.0469970703125,
-0.01236724853515625,
-0.0157623291015625,
-0.005706787109375,
-0.0228271484375,
-0.0119476318359375,
-0.0033416748046875,
-0.054962158203125,
0.022735595703125,
0.03265380859375,
-0.045745849609375,
-0.02008056640625,
-0.044219970703125,
0... |
CrucibleAI/ControlNetMediaPipeFace | 2023-05-19T19:32:02.000Z | [
"diffusers",
"controlnet",
"laion",
"face",
"mediapipe",
"image-to-image",
"en",
"dataset:LAION-Face",
"dataset:LAION",
"arxiv:2302.05543",
"arxiv:2112.10752",
"arxiv:2210.08402",
"license:openrail",
"has_space",
"diffusers:ControlNetModel",
"region:us"
] | image-to-image | CrucibleAI | null | null | CrucibleAI/ControlNetMediaPipeFace | 479 | 2,598 | diffusers | 2023-03-30T18:28:07 | ---
language:
- en
thumbnail: ''
tags:
- controlnet
- laion
- face
- mediapipe
- image-to-image
license: openrail
base_model: stabilityai/stable-diffusion-2-1-base
datasets:
- LAION-Face
- LAION
pipeline_tag: image-to-image
---
# ControlNet LAION Face Dataset
## Table of Contents:
- Overview: Samples, Contents, and C... | 11,101 | [
[
-0.032470703125,
-0.022430419921875,
-0.005970001220703125,
0.0157470703125,
-0.01043701171875,
-0.01995849609375,
0.00005692243576049805,
-0.021728515625,
0.040130615234375,
0.042877197265625,
-0.050689697265625,
-0.03741455078125,
-0.04443359375,
-0.012115... |
digiplay/VoidnoiseCore_R0829 | 2023-08-20T17:55:33.000Z | [
"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/VoidnoiseCore_R0829 | 2 | 2,597 | diffusers | 2023-08-20T17:07:38 | ---
license: other
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
inference: true
---
Model info :
https://civitai.com/models/131565?modelVersionId=144629
![00005-483248321 (1).jpeg](https://cdn-uploads.huggingface.co/production/uploads/646c83c871d0c8a6e4455854/wzAP-zQg5fkjhRHu7IqQ... | 447 | [
[
-0.041748046875,
-0.007411956787109375,
0.0166778564453125,
0.0209503173828125,
-0.03631591796875,
0.0007767677307128906,
0.0273284912109375,
-0.019287109375,
0.051025390625,
0.02545166015625,
-0.0545654296875,
-0.0156402587890625,
-0.02130126953125,
-0.0116... |
lucasresck/bert-base-cased-ag-news | 2021-11-09T02:11:29.000Z | [
"transformers",
"pytorch",
"bert",
"text-classification",
"classification",
"en",
"dataset:ag_news",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-classification | lucasresck | null | null | lucasresck/bert-base-cased-ag-news | 2 | 2,594 | transformers | 2022-03-02T23:29:05 | ---
language:
- en
license: mit
tags:
- bert
- classification
datasets:
- ag_news
metrics:
- accuracy
- f1
- recall
- precision
widget:
- text: "Is it soccer or football?"
example_title: "Sports"
- text: "A new version of Ubuntu was released."
example_title: "Sci/Tech"
---
# bert-base-cased-ag-news
BERT model fin... | 1,643 | [
[
-0.02197265625,
-0.05120849609375,
0.0091094970703125,
0.00734710693359375,
-0.0198211669921875,
-0.0086517333984375,
-0.00531005859375,
-0.0224761962890625,
0.0211181640625,
0.0059967041015625,
-0.035247802734375,
-0.0496826171875,
-0.0643310546875,
-0.0163... |
timm/edgenext_base.usi_in1k | 2023-04-23T22:42:59.000Z | [
"timm",
"pytorch",
"safetensors",
"image-classification",
"dataset:imagenet-1k",
"arxiv:2206.10589",
"arxiv:2204.03475",
"license:mit",
"region:us"
] | image-classification | timm | null | null | timm/edgenext_base.usi_in1k | 0 | 2,594 | timm | 2023-04-23T22:42:43 | ---
tags:
- image-classification
- timm
library_name: timm
license: mit
datasets:
- imagenet-1k
---
# Model card for edgenext_base.usi_in1k
An EdgeNeXt image classification model. Trained on ImageNet-1k by paper authors using distillation (`USI` as per `Solving ImageNet`).
## Model Details
- **Model Type:** Image cla... | 4,428 | [
[
-0.044525146484375,
-0.02862548828125,
0.0008707046508789062,
0.001972198486328125,
-0.0249481201171875,
-0.0233306884765625,
-0.0121307373046875,
-0.032623291015625,
0.00714111328125,
0.0275726318359375,
-0.039825439453125,
-0.0528564453125,
-0.04815673828125,
... |
GroNLP/hateBERT | 2023-06-02T14:04:39.000Z | [
"transformers",
"pytorch",
"safetensors",
"bert",
"fill-mask",
"HateBERT",
"text classification",
"abusive language",
"hate speech",
"offensive language",
"en",
"autotrain_compatible",
"endpoints_compatible",
"region:us",
"has_space"
] | fill-mask | GroNLP | null | null | GroNLP/hateBERT | 22 | 2,592 | transformers | 2022-03-02T23:29:04 | ---
language: en
tags:
- HateBERT
- text classification
- abusive language
- hate speech
- offensive language
---
#
[Tommaso Caselli](https://www.semanticscholar.org/author/Tommaso-Caselli/1864635) •
[Valerio Basile](https://www.semanticscholar.org/author/Valerio-Basile/3101511) •
[Jelena Mitrovic](https://www.semant... | 2,469 | [
[
-0.0318603515625,
-0.06512451171875,
0.01493072509765625,
0.0091400146484375,
-0.017913818359375,
-0.026519775390625,
-0.0231781005859375,
-0.054534912109375,
0.015838623046875,
0.024505615234375,
-0.0173797607421875,
-0.03875732421875,
-0.07025146484375,
-0... |
nvidia/segformer-b5-finetuned-cityscapes-1024-1024 | 2022-08-09T11:29:37.000Z | [
"transformers",
"pytorch",
"tf",
"segformer",
"vision",
"image-segmentation",
"dataset:cityscapes",
"arxiv:2105.15203",
"license:other",
"endpoints_compatible",
"has_space",
"region:us"
] | image-segmentation | nvidia | null | null | nvidia/segformer-b5-finetuned-cityscapes-1024-1024 | 15 | 2,592 | transformers | 2022-03-02T23:29:05 | ---
license: other
tags:
- vision
- image-segmentation
datasets:
- cityscapes
widget:
- src: https://cdn-media.huggingface.co/Inference-API/Sample-results-on-the-Cityscapes-dataset-The-above-images-show-how-our-method-can-handle.png
example_title: Road
---
# SegFormer (b5-sized) model fine-tuned on CityScapes
SegFo... | 3,136 | [
[
-0.06695556640625,
-0.05218505859375,
0.0169830322265625,
0.019775390625,
-0.0213470458984375,
-0.02520751953125,
-0.0002799034118652344,
-0.0506591796875,
0.0205535888671875,
0.043182373046875,
-0.06256103515625,
-0.04620361328125,
-0.051239013671875,
0.012... |
facebook/timesformer-hr-finetuned-k400 | 2022-12-12T12:52:40.000Z | [
"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-hr-finetuned-k400 | 1 | 2,591 | transformers | 2022-10-07T22:11:12 | ---
license: "cc-by-nc-4.0"
tags:
- vision
- video-classification
---
# TimeSformer (high-resolution variant, 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 f... | 1,937 | [
[
-0.022003173828125,
-0.0401611328125,
0.0244903564453125,
0.00955963134765625,
-0.0099639892578125,
0.00940704345703125,
-0.0005893707275390625,
-0.0079803466796875,
-0.0003333091735839844,
-0.007175445556640625,
-0.05712890625,
-0.0289306640625,
-0.060791015625... |
keremberke/yolov8s-shoe-classification | 2023-02-22T13:05:11.000Z | [
"ultralytics",
"tensorboard",
"v8",
"ultralyticsplus",
"yolov8",
"yolo",
"vision",
"image-classification",
"pytorch",
"awesome-yolov8-models",
"dataset:keremberke/shoe-classification",
"model-index",
"region:us"
] | image-classification | keremberke | null | null | keremberke/yolov8s-shoe-classification | 0 | 2,591 | ultralytics | 2023-01-30T06:33:06 |
---
tags:
- ultralyticsplus
- yolov8
- ultralytics
- yolo
- vision
- image-classification
- pytorch
- awesome-yolov8-models
library_name: ultralytics
library_version: 8.0.23
inference: false
datasets:
- keremberke/shoe-classification
model-index:
- name: keremberke/yolov8s-shoe-classification
results:
- task:
... | 1,761 | [
[
-0.031829833984375,
-0.0131378173828125,
0.031494140625,
-0.010345458984375,
-0.037200927734375,
-0.01036834716796875,
-0.0001709461212158203,
-0.04296875,
0.00888824462890625,
0.0071868896484375,
-0.035064697265625,
-0.04620361328125,
-0.039886474609375,
-0... |
vilsonrodrigues/falcon-7b-sharded | 2023-07-13T12:48:29.000Z | [
"transformers",
"safetensors",
"falcon",
"text-generation",
"custom_code",
"en",
"dataset:tiiuae/falcon-refinedweb",
"arxiv:2205.14135",
"arxiv:1911.02150",
"arxiv:2101.00027",
"arxiv:2005.14165",
"arxiv:2104.09864",
"arxiv:2306.01116",
"license:apache-2.0",
"text-generation-inference",
... | text-generation | vilsonrodrigues | null | null | vilsonrodrigues/falcon-7b-sharded | 4 | 2,590 | transformers | 2023-06-16T00:24:45 | ---
datasets:
- tiiuae/falcon-refinedweb
language:
- en
inference: false
license: apache-2.0
---
# Resharded
Resharded version of https://huggingface.co/tiiuae/falcon-7b for low RAM enviroments (e.g. Colab, Kaggle) in safetensors
# 🚀 Falcon-7B
**Falcon-7B is a 7B parameters causal decoder-only model built by [TII]... | 10,574 | [
[
-0.04443359375,
-0.061920166015625,
0.0035533905029296875,
0.020477294921875,
-0.01091766357421875,
-0.002376556396484375,
-0.0116729736328125,
-0.037811279296875,
0.020294189453125,
0.0267181396484375,
-0.03582763671875,
-0.034912109375,
-0.058319091796875,
... |
Fantasy-Studio/Paint-by-Example | 2022-12-07T10:44:13.000Z | [
"diffusers",
"stable-diffusion",
"arxiv:2211.13227",
"license:creativeml-openrail-m",
"has_space",
"diffusers:PaintByExamplePipeline",
"region:us"
] | null | Fantasy-Studio | null | null | Fantasy-Studio/Paint-by-Example | 32 | 2,587 | diffusers | 2022-11-27T16:51:40 | ---
license: creativeml-openrail-m
tags:
- stable-diffusion
inference: false
---
# Paint-By-Example
## Overview
[Paint by Example: Exemplar-based Image Editing with Diffusion Models](https://arxiv.org/abs/2211.13227) by Binxin Yang, Shuyang Gu, Bo Zhang, Ting Zhang, Xuejin Chen, Xiaoyan Sun, Dong Chen, Fang Wen
The ... | 3,265 | [
[
-0.037811279296875,
-0.051666259765625,
0.026092529296875,
0.025787353515625,
-0.01485443115234375,
0.0113525390625,
-0.0022411346435546875,
-0.03009033203125,
0.0221405029296875,
0.036773681640625,
-0.050140380859375,
-0.0223541259765625,
-0.05029296875,
-0... |
nvidia/segformer-b4-finetuned-ade-512-512 | 2022-08-06T10:25:42.000Z | [
"transformers",
"pytorch",
"tf",
"segformer",
"vision",
"image-segmentation",
"dataset:scene_parse_150",
"arxiv:2105.15203",
"license:other",
"endpoints_compatible",
"region:us"
] | image-segmentation | nvidia | null | null | nvidia/segformer-b4-finetuned-ade-512-512 | 1 | 2,585 | transformers | 2022-03-02T23:29:05 | ---
license: other
tags:
- vision
- image-segmentation
datasets:
- scene_parse_150
widget:
- src: https://huggingface.co/datasets/hf-internal-testing/fixtures_ade20k/resolve/main/ADE_val_00000001.jpg
example_title: House
- src: https://huggingface.co/datasets/hf-internal-testing/fixtures_ade20k/resolve/main/ADE_val_0... | 3,209 | [
[
-0.06707763671875,
-0.053741455078125,
0.01385498046875,
0.0155792236328125,
-0.0234222412109375,
-0.0262451171875,
0.0001932382583618164,
-0.051116943359375,
0.0223846435546875,
0.043121337890625,
-0.06561279296875,
-0.043487548828125,
-0.056610107421875,
0... |
Helsinki-NLP/opus-mt-lv-en | 2023-08-16T12:00:49.000Z | [
"transformers",
"pytorch",
"tf",
"marian",
"text2text-generation",
"translation",
"lv",
"en",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | translation | Helsinki-NLP | null | null | Helsinki-NLP/opus-mt-lv-en | 0 | 2,584 | transformers | 2022-03-02T23:29:04 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-lv-en
* source languages: lv
* target languages: en
* OPUS readme: [lv-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/lv-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... | 907 | [
[
-0.020965576171875,
-0.0287933349609375,
0.022857666015625,
0.0241241455078125,
-0.028900146484375,
-0.025665283203125,
-0.0291900634765625,
-0.0041351318359375,
0.00321197509765625,
0.035675048828125,
-0.056427001953125,
-0.041046142578125,
-0.039093017578125,
... |
jonatasgrosman/wav2vec2-xls-r-1b-portuguese | 2022-12-14T02:02:02.000Z | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_8_0",
"pt",
"robust-speech-event",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"has_space",
"region:... | automatic-speech-recognition | jonatasgrosman | null | null | jonatasgrosman/wav2vec2-xls-r-1b-portuguese | 9 | 2,581 | transformers | 2022-03-02T23:29:05 | ---
language:
- pt
license: apache-2.0
tags:
- automatic-speech-recognition
- hf-asr-leaderboard
- mozilla-foundation/common_voice_8_0
- pt
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_8_0
model-index:
- name: XLS-R Wav2Vec2 Portuguese by Jonatas Grosman
results:
- task:
name: Automatic S... | 4,543 | [
[
-0.0264892578125,
-0.052398681640625,
0.01181793212890625,
0.0219573974609375,
-0.01519012451171875,
-0.01727294921875,
-0.0311737060546875,
-0.043487548828125,
0.00815582275390625,
0.024200439453125,
-0.0345458984375,
-0.043731689453125,
-0.048797607421875,
... |
ramsrigouthamg/t5-large-paraphraser-diverse-high-quality | 2021-09-21T05:21:49.000Z | [
"transformers",
"pytorch",
"t5",
"text2text-generation",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text2text-generation | ramsrigouthamg | null | null | ramsrigouthamg/t5-large-paraphraser-diverse-high-quality | 24 | 2,577 | transformers | 2022-03-02T23:29:05 | Blog post with more details as well as easy to use Google Colab link: https://towardsdatascience.com/high-quality-sentence-paraphraser-using-transformers-in-nlp-c33f4482856f
!pip install transformers==4.10.2
!pip install sentencepiece==0.1.96
```
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
model =... | 1,787 | [
[
-0.016387939453125,
-0.050079345703125,
0.029449462890625,
0.0411376953125,
-0.033660888671875,
0.005031585693359375,
0.00809478759765625,
-0.0020847320556640625,
0.00875091552734375,
0.0313720703125,
-0.025054931640625,
-0.0208892822265625,
-0.051605224609375,
... |
IDEA-CCNL/Taiyi-Stable-Diffusion-1B-Chinese-v0.1 | 2023-05-25T09:27:55.000Z | [
"diffusers",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"zh",
"Chinese",
"arxiv:2112.10752",
"arxiv:2209.02970",
"license:creativeml-openrail-m",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | IDEA-CCNL | null | null | IDEA-CCNL/Taiyi-Stable-Diffusion-1B-Chinese-v0.1 | 412 | 2,577 | diffusers | 2022-10-31T12:23:38 | ---
language: zh
license: creativeml-openrail-m
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- zh
- Chinese
inference: true
widget:
- text: "孤帆远影碧空尽，惟见长江天际流,油画"
example_title: 孤帆远影碧空尽，惟见长江天际流,油画
- text: "日出在印象的港口来回, 唯美, 插画"
example_title: 日出在印象的港口来回, 唯美, 插画
- text: "科幻, 外星文明, 建筑, 机械感, 4k壁... | 7,489 | [
[
-0.030517578125,
-0.0634765625,
0.0262298583984375,
0.02850341796875,
-0.035797119140625,
-0.0233001708984375,
-0.0262298583984375,
-0.02239990234375,
0.03033447265625,
0.01245880126953125,
-0.025238037109375,
-0.05230712890625,
-0.039215087890625,
-0.004703... |
Yntec/Darkside | 2023-09-29T07:52:19.000Z | [
"diffusers",
"Anime",
"Horror",
"Pixar",
"DucHaiten",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"license:creativeml-openrail-m",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | Yntec | null | null | Yntec/Darkside | 1 | 2,577 | diffusers | 2023-09-29T06:54:29 | ---
license: creativeml-openrail-m
library_name: diffusers
pipeline_tag: text-to-image
tags:
- Anime
- Horror
- Pixar
- DucHaiten
- stable-diffusion
- stable-diffusion-diffusers
- diffusers
- text-to-image
---
# DucHaiten Darkside
fp16 no-ema version of this model: https://civitai.com/models/5426?modelVersionId=6311... | 857 | [
[
-0.04083251953125,
-0.07135009765625,
0.0190887451171875,
0.011627197265625,
-0.0261688232421875,
-0.00380706787109375,
0.0163421630859375,
-0.032501220703125,
0.0841064453125,
0.044189453125,
-0.051910400390625,
-0.053955078125,
-0.03253173828125,
0.0082702... |
TheBloke/CodeLlama-13B-Instruct-GPTQ | 2023-09-27T12:46:10.000Z | [
"transformers",
"safetensors",
"llama",
"text-generation",
"llama-2",
"custom_code",
"code",
"arxiv:2308.12950",
"license:llama2",
"text-generation-inference",
"region:us"
] | text-generation | TheBloke | null | null | TheBloke/CodeLlama-13B-Instruct-GPTQ | 29 | 2,569 | transformers | 2023-08-25T00:51:10 | ---
language:
- code
license: llama2
tags:
- llama-2
model_name: CodeLlama 13B Instruct
base_model: codellama/CodeLlama-13b-Instruct-hf
inference: false
model_creator: Meta
model_type: llama
pipeline_tag: text-generation
prompt_template: '[INST] Write code to solve the following coding problem that obeys
the constrai... | 21,174 | [
[
-0.0347900390625,
-0.06085205078125,
0.01155853271484375,
0.0092926025390625,
-0.024627685546875,
-0.00972747802734375,
0.0025196075439453125,
-0.035369873046875,
0.01201629638671875,
0.0273590087890625,
-0.044158935546875,
-0.042572021484375,
-0.024398803710937... |
timm/resnest50d.in1k | 2023-04-23T23:35:49.000Z | [
"timm",
"pytorch",
"safetensors",
"image-classification",
"dataset:imagenet-1k",
"arxiv:2004.08955",
"license:apache-2.0",
"region:us"
] | image-classification | timm | null | null | timm/resnest50d.in1k | 0 | 2,568 | timm | 2023-04-23T23:35:20 | ---
tags:
- image-classification
- timm
library_name: timm
license: apache-2.0
datasets:
- imagenet-1k
---
# Model card for resnest50d.in1k
A ResNeSt (ResNet based architecture with Split Attention) image classification model. Trained on ImageNet-1k by paper authors.
## Model Details
- **Model Type:** Image classific... | 3,733 | [
[
-0.042510986328125,
-0.03460693359375,
0.0073699951171875,
0.0110321044921875,
-0.02508544921875,
-0.02374267578125,
-0.0193939208984375,
-0.0210418701171875,
0.0279541015625,
0.036163330078125,
-0.05023193359375,
-0.048126220703125,
-0.04962158203125,
-0.00... |
allenai/t5-small-squad2-question-generation | 2023-01-24T16:27:47.000Z | [
"transformers",
"pytorch",
"jax",
"t5",
"text2text-generation",
"en",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text2text-generation | allenai | null | null | allenai/t5-small-squad2-question-generation | 36 | 2,565 | transformers | 2022-03-02T23:29:05 | ---
language: en
---
A simple question-generation model built based on SQuAD 2.0 dataset.
Example use:
```python
from transformers import T5Config, T5ForConditionalGeneration, T5Tokenizer
model_name = "allenai/t5-small-squad2-question-generation"
tokenizer = T5Tokenizer.from_pretrained(model_name)
model = T5ForCond... | 1,251 | [
[
-0.031951904296875,
-0.043182373046875,
0.033233642578125,
0.0005245208740234375,
-0.034454345703125,
-0.01251983642578125,
-0.0010862350463867188,
-0.0248260498046875,
-0.00128936767578125,
0.0206756591796875,
-0.0911865234375,
-0.0245513916015625,
-0.025115966... |
kakaobrain/kogpt | 2022-09-26T02:17:11.000Z | [
"KakaoBrain",
"KoGPT",
"GPT",
"GPT3",
"ko",
"arxiv:2104.09864",
"arxiv:2109.04650",
"license:cc-by-nc-4.0",
"has_space",
"region:us"
] | null | kakaobrain | null | null | kakaobrain/kogpt | 92 | 2,564 | null | 2022-03-02T23:29:05 | ---
language: ko
tags:
- KakaoBrain
- KoGPT
- GPT
- GPT3
license: cc-by-nc-4.0
---
# KoGPT
KakaoBrain's Pre-Trained Language Models.
* KoGPT (Korean Generative Pre-trained Transformer)
* [https://github.com/kakaobrain/kogpt](https://github.com/kakaobrain/kogpt)
* [https://huggingface.co/kakaobrain/kogpt](https:... | 7,743 | [
[
-0.041412353515625,
-0.0496826171875,
0.0232696533203125,
0.0199432373046875,
-0.039703369140625,
-0.009674072265625,
-0.016143798828125,
-0.0161590576171875,
0.006168365478515625,
0.0231475830078125,
-0.034210205078125,
-0.037872314453125,
-0.05023193359375,
... |
google/bert_uncased_L-8_H-512_A-8 | 2021-05-19T17:35:53.000Z | [
"transformers",
"pytorch",
"jax",
"bert",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | google | null | null | google/bert_uncased_L-8_H-512_A-8 | 3 | 2,562 | transformers | 2022-03-02T23:29:05 | ---
thumbnail: https://huggingface.co/front/thumbnails/google.png
license: apache-2.0
---
BERT Miniatures
===
This is the set of 24 BERT models referenced in [Well-Read Students Learn Better: On the Importance of Pre-training Compact Models](https://arxiv.org/abs/1908.08962) (English only, uncased, trained with Word... | 4,617 | [
[
-0.053558349609375,
-0.03546142578125,
0.0239410400390625,
0.0131683349609375,
-0.0237274169921875,
-0.016937255859375,
-0.02398681640625,
-0.031219482421875,
0.04376220703125,
-0.006107330322265625,
-0.06103515625,
-0.030670166015625,
-0.05206298828125,
-0.... |
google/pegasus-multi_news | 2023-01-24T16:42:34.000Z | [
"transformers",
"pytorch",
"pegasus",
"text2text-generation",
"summarization",
"en",
"arxiv:1912.08777",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | summarization | google | null | null | google/pegasus-multi_news | 10 | 2,561 | transformers | 2022-03-02T23:29:05 | ---
language: en
tags:
- summarization
---
### Pegasus Models
See Docs: [here](https://huggingface.co/transformers/master/model_doc/pegasus.html)
Original TF 1 code [here](https://github.com/google-research/pegasus)
Authors: Jingqing Zhang, Yao Zhao, Mohammad Saleh and Peter J. Liu on Dec 18, 2019
Maintained by: [@... | 3,332 | [
[
-0.0284423828125,
-0.05816650390625,
0.0289306640625,
0.02069091796875,
-0.0264892578125,
-0.0251007080078125,
-0.01071929931640625,
-0.033721923828125,
0.0394287109375,
0.0221405029296875,
-0.058349609375,
-0.045867919921875,
-0.054779052734375,
-0.00140571... |
anjali0610/my-dog | 2023-10-24T17:20:01.000Z | [
"diffusers",
"NxtWave-GenAI-Webinar",
"text-to-image",
"stable-diffusion",
"license:creativeml-openrail-m",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"region:us",
"has_space"
] | text-to-image | anjali0610 | null | null | anjali0610/my-dog | 0 | 2,561 | diffusers | 2023-10-24T17:14:45 | ---
license: creativeml-openrail-m
tags:
- NxtWave-GenAI-Webinar
- text-to-image
- stable-diffusion
---
### My-Dog Dreambooth model trained by anjali0610 following the "Build your own Gen AI model" session by NxtWave.
Project Submission Code: CCEW-122
Sample pictures of this concept:
![0](https://huggingface.co/an... | 383 | [
[
-0.054443359375,
-0.0164947509765625,
0.0277557373046875,
0.0009636878967285156,
-0.0088348388671875,
0.03485107421875,
0.03790283203125,
-0.034942626953125,
0.039215087890625,
0.0275726318359375,
-0.049591064453125,
-0.0263824462890625,
-0.021514892578125,
... |
M-CLIP/M-BERT-Base-ViT-B | 2021-05-18T21:34:39.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"bert",
"feature-extraction",
"endpoints_compatible",
"region:us"
] | feature-extraction | M-CLIP | null | null | M-CLIP/M-BERT-Base-ViT-B | 10 | 2,560 | transformers | 2022-03-02T23:29:04 | <br />
<p align="center">
<h1 align="center">M-BERT Base ViT-B</h1>
<p align="center">
<a href="https://github.com/FreddeFrallan/Multilingual-CLIP/tree/main/Model%20Cards/M-BERT%20Base%20ViT-B">Github Model Card</a>
</p>
</p>
## Usage
To use this model along with the original CLIP vision encoder you nee... | 2,162 | [
[
-0.031982421875,
-0.032073974609375,
0.014923095703125,
0.0158843994140625,
-0.041046142578125,
0.0075836181640625,
-0.038604736328125,
-0.0254364013671875,
0.03546142578125,
0.0178375244140625,
-0.04901123046875,
-0.046844482421875,
-0.045379638671875,
0.00... |
TencentARC/t2i-adapter-depth-midas-sdxl-1.0 | 2023-09-07T19:11:24.000Z | [
"diffusers",
"art",
"t2i-adapter",
"image-to-image",
"stable-diffusion-xl-diffusers",
"stable-diffusion-xl",
"arxiv:2302.08453",
"license:apache-2.0",
"has_space",
"diffusers:T2IAdapter",
"region:us"
] | image-to-image | TencentARC | null | null | TencentARC/t2i-adapter-depth-midas-sdxl-1.0 | 8 | 2,558 | diffusers | 2023-09-03T14:46:44 | ---
license: apache-2.0
base_model: stabilityai/stable-diffusion-xl-base-1.0
tags:
- art
- t2i-adapter
- image-to-image
- stable-diffusion-xl-diffusers
- stable-diffusion-xl
---
# T2I-Adapter-SDXL - Depth-MiDaS
T2I Adapter is a network providing additional conditioning to stable diffusion. Each t2i checkpoint takes a... | 8,957 | [
[
-0.0477294921875,
-0.0283203125,
0.026641845703125,
0.032501220703125,
-0.0338134765625,
-0.0196075439453125,
0.01085662841796875,
-0.03363037109375,
0.042877197265625,
-0.000621795654296875,
-0.055511474609375,
-0.036224365234375,
-0.048675537109375,
-0.008... |
stablediffusionapi/NightVision_XL | 2023-10-06T19:25:07.000Z | [
"diffusers",
"stablediffusionapi.com",
"stable-diffusion-api",
"text-to-image",
"ultra-realistic",
"license:creativeml-openrail-m",
"endpoints_compatible",
"diffusers:StableDiffusionXLPipeline",
"region:us"
] | text-to-image | stablediffusionapi | null | null | stablediffusionapi/NightVision_XL | 2 | 2,558 | diffusers | 2023-10-06T19:23:18 | ---
license: creativeml-openrail-m
tags:
- stablediffusionapi.com
- stable-diffusion-api
- text-to-image
- ultra-realistic
pinned: true
---
# NightVision XL API Inference
![generated from stablediffusionapi.com](https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/83a41e5b-63ae-46a7-9202-c3b8170598a6/width=1280/0... | 2,519 | [
[
-0.028717041015625,
-0.055511474609375,
0.040435791015625,
0.017333984375,
-0.03887939453125,
0.006900787353515625,
0.024993896484375,
-0.0390625,
0.035797119140625,
0.0535888671875,
-0.05621337890625,
-0.06732177734375,
-0.026947021484375,
0.003202438354492... |
albert-xlarge-v2 | 2021-01-13T15:34:57.000Z | [
"transformers",
"pytorch",
"tf",
"albert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | null | null | null | albert-xlarge-v2 | 3 | 2,549 | transformers | 2022-03-02T23:29:04 | ---
language: en
license: apache-2.0
datasets:
- bookcorpus
- wikipedia
---
# ALBERT XLarge v2
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1909.11942) and first released in
[this repository](https://github.com/google-re... | 9,766 | [
[
-0.00820159912109375,
-0.0379638671875,
0.0192413330078125,
0.021392822265625,
-0.030242919921875,
0.0034198760986328125,
0.01157379150390625,
-0.01529693603515625,
0.0251007080078125,
0.04730224609375,
-0.0428466796875,
-0.032928466796875,
-0.06304931640625,
... |
tner/roberta-large-tweetner7-all | 2022-09-27T15:29:57.000Z | [
"transformers",
"pytorch",
"roberta",
"token-classification",
"dataset:tner/tweetner7",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | token-classification | tner | null | null | tner/roberta-large-tweetner7-all | 0 | 2,543 | transformers | 2022-07-02T19:08:51 | ---
datasets:
- tner/tweetner7
metrics:
- f1
- precision
- recall
model-index:
- name: tner/roberta-large-tweetner7-all
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: tner/tweetner7
type: tner/tweetner7
args: tner/tweetner7
metrics:
- ... | 8,064 | [
[
-0.031768798828125,
-0.054229736328125,
0.0213775634765625,
0.01326751708984375,
-0.01128387451171875,
0.0011262893676757812,
-0.0430908203125,
-0.03564453125,
0.033935546875,
0.0238494873046875,
-0.043701171875,
-0.04901123046875,
-0.054595947265625,
0.0130... |
CATIE-AQ/QAmembert | 2023-10-18T08:30:06.000Z | [
"transformers",
"pytorch",
"safetensors",
"camembert",
"question-answering",
"fr",
"dataset:etalab-ia/piaf",
"dataset:fquad",
"dataset:lincoln/newsquadfr",
"dataset:pragnakalp/squad_v2_french_translated",
"dataset:CATIE-AQ/frenchQA",
"arxiv:1910.09700",
"doi:10.57967/hf/0821",
"license:cc-... | question-answering | CATIE-AQ | null | null | CATIE-AQ/QAmembert | 12 | 2,542 | transformers | 2023-01-10T16:33:26 | ---
language: fr
datasets:
- etalab-ia/piaf
- fquad
- lincoln/newsquadfr
- pragnakalp/squad_v2_french_translated
- CATIE-AQ/frenchQA
widget:
- text: Combien de personnes utilisent le français tous les jours ?
context: >-
Le français est une langue indo-européenne de la famille des langues romanes
dont les loc... | 10,538 | [
[
-0.0399169921875,
-0.041259765625,
0.021697998046875,
0.02264404296875,
0.001575469970703125,
-0.0015611648559570312,
-0.0012388229370117188,
-0.016326904296875,
0.0233001708984375,
0.024444580078125,
-0.061370849609375,
-0.035858154296875,
-0.0237884521484375,
... |
Yntec/a-ZovyaRPGV3VAE | 2023-08-03T16:21:10.000Z | [
"diffusers",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"Zovya",
"license:creativeml-openrail-m",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | Yntec | null | null | Yntec/a-ZovyaRPGV3VAE | 0 | 2,541 | diffusers | 2023-08-03T16:04:42 | ---
license: creativeml-openrail-m
library_name: diffusers
pipeline_tag: text-to-image
tags:
- stable-diffusion
- stable-diffusion-diffusers
- diffusers
- text-to-image
- Zovya
---
# A-Zovya RPG Artist Tools V3 VAE
Original page:
https://civitai.com/models/8124?modelVersionId=87886
| 287 | [
[
-0.01457977294921875,
0.0032806396484375,
0.043853759765625,
0.03240966796875,
-0.036285400390625,
-0.0156402587890625,
0.044189453125,
-0.0031108856201171875,
0.03369140625,
0.066650390625,
-0.09161376953125,
-0.046142578125,
-0.00788116455078125,
-0.020721... |
infgrad/stella-base-zh | 2023-10-19T06:59:19.000Z | [
"transformers",
"pytorch",
"bert",
"feature-extraction",
"mteb",
"arxiv:1612.00796",
"model-index",
"endpoints_compatible",
"region:us"
] | feature-extraction | infgrad | null | null | infgrad/stella-base-zh | 9 | 2,537 | transformers | 2023-09-09T15:15:44 | ---
tags:
- mteb
model-index:
- name: stella-base-zh
results:
- task:
type: STS
dataset:
type: C-MTEB/AFQMC
name: MTEB AFQMC
config: default
split: validation
revision: None
metrics:
- type: cos_sim_pearson
value: 49.34825050234731
- type: cos_sim_spearman
... | 37,851 | [
[
-0.0256805419921875,
-0.0545654296875,
0.023712158203125,
0.035675048828125,
-0.0227508544921875,
-0.0205841064453125,
-0.0137939453125,
-0.026885986328125,
0.02508544921875,
0.0178070068359375,
-0.0455322265625,
-0.060150146484375,
-0.047576904296875,
0.016... |
kyujinpy/KoT-platypus2-7B | 2023-10-19T13:28:38.000Z | [
"transformers",
"pytorch",
"llama",
"text-generation",
"ko",
"dataset:kyujinpy/KoCoT_2000",
"license:cc-by-nc-sa-4.0",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | kyujinpy | null | null | kyujinpy/KoT-platypus2-7B | 6 | 2,537 | transformers | 2023-09-29T15:19:22 | ---
language:
- ko
datasets:
- kyujinpy/KoCoT_2000
library_name: transformers
pipeline_tag: text-generation
license: cc-by-nc-sa-4.0
---
**(주)미디어그룹사람과숲과 (주)마커의 LLM 연구 컨소시엄에서 개발된 모델입니다**
**The license is `cc-by-nc-sa-4.0`.**
# **KoT-platypus2**
**CoT + KO-platypus2 = KoT-platypus2**... | 6,000 | [
[
-0.04791259765625,
-0.0477294921875,
0.0201873779296875,
0.03509521484375,
-0.04736328125,
0.014251708984375,
-0.01003265380859375,
-0.038909912109375,
0.060302734375,
0.005153656005859375,
-0.0250091552734375,
-0.044677734375,
-0.054351806640625,
0.01882934... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.