modelId stringlengths 4 81 | tags list | pipeline_tag stringclasses 17
values | config dict | downloads int64 0 59.7M | first_commit timestamp[ns, tz=UTC] | card stringlengths 51 438k | embedding list |
|---|---|---|---|---|---|---|---|
Dizoid/Lll | [] | null | {
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library_name: keras
---
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
| Hyperparameters ... | [
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Dkwkk/Da | [] | null | {
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library_name: keras
---
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training Metrics
Model history needed
## Model Plot
<details>
<summary>View Model Plot</summary>
![Model Image](./model.pn... | [
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Dkwkk/W | [] | null | {
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library_name: keras
---
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Model Plot
<details>
<summary>View Model Plot</summary>
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Dmitriiserg/Pxd | [] | null | {
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library_name: keras
---
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
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Dmitry12/sber | [] | null | {
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library_name: keras
---
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
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Doogie/Waynehills-KE-T5-doogie | [] | null | {
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license: apache-2.0
tags:
- image-classification
- keras
library_name: keras
---
Keras Dog vs Cat based on the [official Keras documentation](https://keras.io/examples/vision/image_classification_from_scratch/)
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Waynehillsdev/Waynehills_summary_tensorflow | [
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license: apache-2.0
tags:
- image-classification
- keras
library_name: keras
---
# Model Card for nateraw/keras-mobilevit-xxs-flowers
| [
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Doquey/DialoGPT-small-Luisbot1 | [
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"no_repeat_ngram_size... | 7 | null | # Flowers GAN
<a href="https://colab.research.google.com/github/nateraw/huggingface-hub-examples/blob/main/pytorch_lightweight_gan.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
Give the [Github Repo](https://github.com/nateraw/huggingface-hub-exa... | [
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DoyyingFace/bert-asian-hate-tweets-asian-unclean-freeze-4 | [
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"no_rep... | 44 | 2021-11-15T19:59:19Z | ---
tags:
- image-classification
- timm
- generated_from_trainer
library_tag: timm
datasets:
- cats_vs_dogs
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# my-cool-timm-mode... | [
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DoyyingFace/bert-asian-hate-tweets-asian-unclean-freeze-8 | [
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"no_rep... | 30 | null | ---
tags:
- image-classification
- timm
- generated_from_trainer
datasets:
- cats_vs_dogs
model-index:
- name: my-cool-timm-model-3
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove ... | [
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DoyyingFace/bert-asian-hate-tweets-asian-unclean-slanted | [
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"no_rep... | 29 | null | ---
tags:
- image-classification
- timm
library_tag: timm
---
# Model card for my-cool-timm-model | [
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DoyyingFace/bert-asian-hate-tweets-asian-unclean-warmup-100 | [
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"no_rep... | 28 | null | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: pasta-pizza-ravioli
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9375
---
# pasta-pizza-ravioli
Auto... | [
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DoyyingFace/bert-asian-hate-tweets-asian-unclean-warmup-25 | [
"pytorch",
"bert",
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"no_rep... | 30 | null | ---
license: apache-2.0
tags:
- image-classification
- huggingpics
- generated_from_trainer
model-index:
- name: pasta-shapes
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this c... | [
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DoyyingFace/bert-asian-hate-tweets-asian-unclean-warmup-75 | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
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"no_rep... | 37 | 2021-08-23T21:37:57Z | ---
license: apache-2.0
tags:
- huggingpics
- image-classification
- generated_from_trainer
metrics:
- accuracy
model_index:
- name: planes-trains-automobiles
results:
- task:
name: Image Classification
type: image-classification
metric:
name: Accuracy
type: accuracy
value: 0.98507... | [
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DoyyingFace/bert-asian-hate-tweets-asian-unclean-with-clean-valid | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
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"no_rep... | 33 | 2021-10-10T22:20:39Z | ---
tags:
- image-classification
- keras
library_name: keras
---
# Quickdraw Model | [
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DoyyingFace/bert-asian-hate-tweets-asonam-clean | [
"pytorch",
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"transformers"
] | text-classification | {
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"no_rep... | 27 | 2021-09-04T20:45:59Z | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: rare-puppers-09-04-2021
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.8657407164573669
---
# rare-puppe... | [
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DoyyingFace/bert-asian-hate-tweets-asonam-unclean | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | {
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"no_rep... | 30 | 2021-12-10T21:18:34Z | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: rare-puppers-123
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9701492786407471
---
# rare-puppers-123
... | [
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DoyyingFace/bert-asian-hate-tweets-concat-clean-with-unclean-valid | [
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"bert",
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"no_rep... | 25 | null | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: rare-puppers-demo
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9101123809814453
---
# rare-puppers-dem... | [
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DoyyingFace/bert-asian-hate-tweets-concat-clean | [
"pytorch",
"bert",
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"transformers"
] | text-classification | {
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"no_rep... | 25 | null | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: rare-puppers-new-auth
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.89552241563797
---
# rare-puppers-n... | [
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-0.006808749865740538,
0.02909202314913273,
0.033292267471551895,
0.0394124761223793,
-0.007188298739492893,
-0.023504380136728287,
-0.02661443129181862,
-0.01760507933795452,
0.05808568000793457,
0.020287036895751953,
0.0024399810936301947,
0.004003823734819889,
0.03... |
albert-base-v1 | [
"pytorch",
"tf",
"safetensors",
"albert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"transformers",
"exbert",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"AlbertForMaskedLM"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_... | 38,156 | 2021-06-29T20:17:28Z | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: rare-puppers
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9583333134651184
---
# rare-puppers
Autoge... | [
-0.011083164252340794,
-0.0025235607754439116,
0.029570212587714195,
0.03448803350329399,
0.04047790542244911,
-0.008983897976577282,
-0.026590298861265182,
-0.021886948496103287,
-0.023077508434653282,
0.05300625413656235,
0.02642292156815529,
0.0013035284355282784,
0.003618974471464753,
... |
albert-xlarge-v2 | [
"pytorch",
"tf",
"albert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"transformers",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"AlbertForMaskedLM"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_... | 2,973 | 2021-11-23T04:45:30Z | ---
tags:
- image-classification
- timm
library_tag: timm
---
# Model card for resnet18-random-classifier-123 | [
-0.019875245168805122,
-0.01390763744711876,
0.00522333150729537,
-0.0061964718624949455,
0.03111930564045906,
0.0025272464845329523,
-0.0006924316985532641,
0.012991913594305515,
-0.01897396333515644,
0.044547419995069504,
0.025234512984752655,
0.006322748493403196,
-0.017336329445242882,
... |
bert-base-cased-finetuned-mrpc | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 11,644 | 2021-09-22T18:01:31Z | ---
tags:
- image-classification
- timm
- generated_from_trainer
datasets:
- beans
model-index:
- name: model
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: beans
type: beans
args: default
library_tag: timm
---
<!-- This model card has been g... | [
-0.009893117472529411,
-0.005889368709176779,
-0.006551862228661776,
0.03473423793911934,
0.03408208116889,
0.0025062784552574158,
-0.017607731744647026,
-0.017265284433960915,
-0.023414913564920425,
0.058449145406484604,
0.032290488481521606,
-0.004401441663503647,
-0.017777252942323685,
... |
bert-base-cased | [
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1810.04805",
"transformers",
"exbert",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 8,621,271 | 2021-12-03T06:29:58Z | ---
tags:
- image-classification
- timm
library_tag: timm
---
# Model card for resnet50-oxford-iiit-pet
 | [
0.0055904509499669075,
-0.005331485532224178,
0.011549311690032482,
0.006632516160607338,
0.02979063056409359,
0.01595914736390114,
-0.014076166786253452,
0.005919062532484531,
-0.02137773111462593,
0.05284087732434273,
0.011962753720581532,
-0.009953518398106098,
-0.00837852992117405,
0.0... |
bert-base-chinese | [
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"fill-mask",
"zh",
"arxiv:1810.04805",
"transformers",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 3,377,486 | 2021-04-13T09:38:42Z | ---
tags:
- image-classification
- pytorch
datasets:
- imagenet
---
# Resnet50 Model from Torchvision
## Using the model
```
pip install modelz
```
```python
from modelz import ResnetModel
model = ResnetModel.from_pretrained('nateraw/resnet50')
ex_input = torch.rand(4, 3, 224, 224)
out = model(ex_input)
``` | [
-0.014441344887018204,
-0.007066982798278332,
0.003675918560475111,
0.024101318791508675,
0.038339968770742416,
-0.00016989049618132412,
-0.025550952181220055,
0.014621231704950333,
-0.025797164067626,
0.05220641568303108,
0.03133575990796089,
0.010230209678411484,
-0.0157686248421669,
0.0... |
bert-base-german-dbmdz-uncased | [
"pytorch",
"jax",
"safetensors",
"bert",
"fill-mask",
"de",
"transformers",
"license:mit",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 68,305 | 2021-09-28T01:56:21Z | ---
tags:
- image-classification
library_name: generic
---
# Test | [
-0.0035932583268731833,
-0.02044888585805893,
0.01147062610834837,
0.009557006880640984,
0.048661183565855026,
-0.006832353305071592,
-0.01230387482792139,
0.021091513335704803,
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0.0326104499399662,
0.019727231934666634,
0.00836354959756136,
-0.014630172401666641,
0.0... |
bert-base-multilingual-uncased | [
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"fill-mask",
"multilingual",
"af",
"sq",
"ar",
"an",
"hy",
"ast",
"az",
"ba",
"eu",
"bar",
"be",
"bn",
"inc",
"bs",
"br",
"bg",
"my",
"ca",
"ceb",
"ce",
"zh",
"cv",
"hr",
"cs",
"da",
"nl",
"en",
"et",
... | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 328,585 | null | ---
tags:
- generated_from_trainer
datasets:
- image_folder
model_index:
- name: test_model_a
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: image_folder
type: image_folder
args: default
---
<!-- This model card has been generated automatical... | [
-0.014186863787472248,
-0.036187440156936646,
-0.00399447325617075,
0.0432218573987484,
0.03092816099524498,
0.006415083538740873,
0.012477558106184006,
-0.021732760593295097,
-0.013156200759112835,
0.04824318736791611,
0.035234663635492325,
-0.00913484301418066,
-0.00907504465430975,
0.05... |
bert-base-uncased | [
"pytorch",
"tf",
"jax",
"rust",
"safetensors",
"bert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1810.04805",
"transformers",
"exbert",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 59,663,489 | 2021-09-28T04:36:26Z | ---
tags:
- text-classification
library_name: generic
---
# Test | [
-0.009605800732970238,
-0.027890324592590332,
0.011636774986982346,
0.015045760199427605,
0.039489999413490295,
0.015606122091412544,
-0.023317888379096985,
0.004809985402971506,
-0.027187751606106758,
0.031392551958560944,
0.02330765500664711,
0.014153067022562027,
-0.005819907411932945,
... |
bert-large-cased-whole-word-masking-finetuned-squad | [
"pytorch",
"tf",
"jax",
"rust",
"safetensors",
"bert",
"question-answering",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1810.04805",
"transformers",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | question-answering | {
"architectures": [
"BertForQuestionAnswering"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_n... | 8,214 | 2021-08-31T21:59:55Z | ---
tags:
- image-classification
- timm
library_tag: timm
---
# Model card for `timm-resnet50-beans`
**TODO**
**For now, try dragging and dropping this image into the inference widget. It should classify as angular_leaf_spot.**
 | [
-0.013562826439738274,
-0.012728719972074032,
-0.00820048525929451,
0.012452923692762852,
0.034371811896562576,
-0.005893999245017767,
-0.0014600733993574977,
0.0045375213958323,
-0.020666878670454025,
0.04689564183354378,
0.013364625163376331,
-0.004525809548795223,
-0.010527686215937138,
... |
distilbert-base-german-cased | [
"pytorch",
"safetensors",
"distilbert",
"fill-mask",
"de",
"transformers",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"DistilBertForMaskedLM"
],
"model_type": "distilbert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repea... | 43,667 | 2021-09-04T01:12:45Z | ---
tags:
- image-classification
- timm
- generated_from_trainer
datasets:
- beans
metrics:
- accuracy
model_index:
- name: timm-resnet18-beans-test-2
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: beans
type: beans
args: default
metric:
... | [
-0.003551504574716091,
-0.0055486117489635944,
-0.011821605265140533,
0.02746102586388588,
0.04920700192451477,
0.004457458853721619,
-0.011709040030837059,
-0.01575721614062786,
-0.02192087657749653,
0.05626164749264717,
0.022083554416894913,
-0.00955709908157587,
-0.017552759498357773,
0... |
distilbert-base-multilingual-cased | [
"pytorch",
"tf",
"onnx",
"safetensors",
"distilbert",
"fill-mask",
"multilingual",
"af",
"sq",
"ar",
"an",
"hy",
"ast",
"az",
"ba",
"eu",
"bar",
"be",
"bn",
"inc",
"bs",
"br",
"bg",
"my",
"ca",
"ceb",
"ce",
"zh",
"cv",
"hr",
"cs",
"da",
"nl",
"en",
... | fill-mask | {
"architectures": [
"DistilBertForMaskedLM"
],
"model_type": "distilbert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repea... | 8,339,633 | 2021-09-04T00:50:49Z | ---
tags:
- image-classification
- timm
- generated_from_trainer
datasets:
- beans
metrics:
- accuracy
model_index:
- name: timm-resnet18-beans-test
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: beans
type: beans
args: default
metric:
... | [
-0.008425991982221603,
0.0011846335837617517,
-0.014359774067997932,
0.027634350582957268,
0.04591516777873039,
0.008714479394257069,
-0.011010638438165188,
-0.014297610148787498,
-0.02147834375500679,
0.054315730929374695,
0.026592377573251724,
-0.009843225590884686,
-0.016252603381872177,
... |
distilbert-base-uncased-distilled-squad | [
"pytorch",
"tf",
"tflite",
"coreml",
"safetensors",
"distilbert",
"question-answering",
"en",
"dataset:squad",
"arxiv:1910.01108",
"arxiv:1910.09700",
"transformers",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | question-answering | {
"architectures": [
"DistilBertForQuestionAnswering"
],
"model_type": "distilbert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 100,097 | 2021-09-27T01:15:47Z | ---
tags:
- image-classification
- timm
library_tag: timm
---
# Model card for timm-resnet18-imagenette-160px-5-epochs | [
-0.010043647140264511,
-0.008584856055676937,
0.007625472266227007,
-0.00807266216725111,
0.03602634370326996,
-0.0017984589794650674,
0.004033443983644247,
0.010819438844919205,
-0.022234151139855385,
0.043249644339084625,
0.026236562058329582,
0.0034453219268471003,
-0.01545056514441967,
... |
distilbert-base-uncased-finetuned-sst-2-english | [
"pytorch",
"tf",
"rust",
"safetensors",
"distilbert",
"text-classification",
"en",
"dataset:sst2",
"dataset:glue",
"arxiv:1910.01108",
"doi:10.57967/hf/0181",
"transformers",
"license:apache-2.0",
"model-index",
"has_space"
] | text-classification | {
"architectures": [
"DistilBertForSequenceClassification"
],
"model_type": "distilbert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 3,060,704 | 2021-10-08T03:14:22Z | ---
tags:
- timm
- image-classification
library_name: timm
---
| [
-0.011224273592233658,
-0.006566904950886965,
0.002445684280246496,
-0.0002786757831927389,
0.039116162806749344,
-0.009473495185375214,
0.005282741971313953,
0.016433902084827423,
-0.01653735153377056,
0.036276668310165405,
0.024509070441126823,
0.002068429719656706,
-0.003856410039588809,
... |
t5-3b | [
"pytorch",
"tf",
"t5",
"text2text-generation",
"en",
"fr",
"ro",
"de",
"multilingual",
"dataset:c4",
"arxiv:1805.12471",
"arxiv:1708.00055",
"arxiv:1704.05426",
"arxiv:1606.05250",
"arxiv:1808.09121",
"arxiv:1810.12885",
"arxiv:1905.10044",
"arxiv:1910.09700",
"transformers",
"... | translation | {
"architectures": [
"T5WithLMHeadModel"
],
"model_type": "t5",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": true,
"length_penalty": 2,
"max_length": 200,
"min_length": 30,
"no_repeat_ngram_size": 3,
... | 103,474 | 2021-10-29T04:04:00Z | ---
tags:
- image-classification
- timm
library_tag: timm
---
# Model card for cait_m48_448 | [
-0.02395196631550789,
-0.001722064451314509,
0.003114119404926896,
0.005489344708621502,
0.020464664325118065,
0.005167373456060886,
-0.0012237000046297908,
0.013372603803873062,
-0.018113600090146065,
0.03845319524407387,
0.02339146099984646,
0.0077932411804795265,
-0.011949768289923668,
... |
t5-base | [
"pytorch",
"tf",
"jax",
"rust",
"safetensors",
"t5",
"text2text-generation",
"en",
"fr",
"ro",
"de",
"dataset:c4",
"arxiv:1805.12471",
"arxiv:1708.00055",
"arxiv:1704.05426",
"arxiv:1606.05250",
"arxiv:1808.09121",
"arxiv:1810.12885",
"arxiv:1905.10044",
"arxiv:1910.09700",
"... | translation | {
"architectures": [
"T5ForConditionalGeneration"
],
"model_type": "t5",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": true,
"length_penalty": 2,
"max_length": 200,
"min_length": 30,
"no_repeat_ngram_s... | 6,339,864 | 2021-10-29T04:22:19Z | ---
tags:
- image-classification
- timm
library_tag: timm
---
# Model card for cait_s24_224 | [
-0.020236250013113022,
-0.006320635322481394,
0.004830471705645323,
0.003668400691822171,
0.026784824207425117,
0.0018779588863253593,
0.0004938854253850877,
0.01496101263910532,
-0.02107251062989235,
0.03845581039786339,
0.023101631551980972,
0.008081325329840183,
-0.011578960344195366,
0... |
xlm-mlm-xnli15-1024 | [
"pytorch",
"tf",
"xlm",
"fill-mask",
"multilingual",
"en",
"fr",
"es",
"de",
"el",
"bg",
"ru",
"tr",
"ar",
"vi",
"th",
"zh",
"hi",
"sw",
"ur",
"arxiv:1901.07291",
"arxiv:1910.09700",
"transformers",
"license:cc-by-nc-4.0",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"XLMWithLMHeadModel"
],
"model_type": "xlm",
"task_specific_params": {
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"no_repeat_ngram_si... | 2,050 | 2021-10-29T04:40:27Z | ---
tags:
- image-classification
- timm
library_tag: timm
---
# Model card for convit_base | [
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AAli/distilbert-base-uncased-finetuned-cola | [] | null | {
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"num_beams... | 0 | 2021-12-09T13:52:39Z | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-base-squad2-distilled-finetuned-chaii-small
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this co... | [
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ATGdev/DialoGPT-small-harrypotter | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
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"no_repeat_ngram_size... | 16 | 2020-10-30T14:15:17Z | ---
language:
- te
tags:
- MaskedLM
- Telugu
- RoBERTa
- Question-Answering
- Token Classification
- Text Classification
---
# Indic-Transformers Telugu RoBERTa
## Model description
This is a RoBERTa language model pre-trained on ~2 GB of monolingual training corpus. The pre-training data was majorly taken from [OSCAR... | [
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AVSilva/bertimbau-large-fine-tuned-md | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"generated_from_trainer",
"license:mit",
"autotrain_compatible"
] | fill-mask | {
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],
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"no_repeat_ngram_size... | 8 | 2020-10-07T13:24:00Z | ---
language: is
datasets:
- Icelandic portion of the OSCAR corpus from INRIA
- oscar
---
# IsRoBERTa a RoBERTa-like masked language model
Probably the first icelandic transformer language model!
## Overview
**Language:** Icelandic
**Downstream-task:** masked-lm
**Training data:** OSCAR corpus
**Code:** See [he... | [
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Abdullaziz/model1 | [] | null | {
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"num_beams... | 0 | 2021-12-15T16:18:53Z | ```python
from transformers import EncoderDecoderModel
from importlib.machinery import SourceFileLoader
from transformers.file_utils import cached_path, hf_bucket_url
import torch
import os
## Load model & tokenizer
cache_dir='./cache'
model_name='nguyenvulebinh/spelling-oov'
def download_tokenizer_files():
resou... | [
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Abozoroov/Me | [] | null | {
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"num_beams... | 0 | 2022-01-17T05:47:32Z | ---
license: mit
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- f1
model-index:
- name: minilm-finetuned-emotion_nm
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
args: default
metrics:
- name: F1
... | [
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AdapterHub/bert-base-uncased-pf-sst2 | [
"bert",
"en",
"arxiv:2104.08247",
"adapter-transformers",
"text-classification",
"adapterhub:sentiment/sst-2"
] | text-classification | {
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"num_bea... | 7 | 2020-12-11T10:58:04Z | ---
language: en
tags:
- tapas
- sequence-classification
license: apache-2.0
---
# TAPAS base model
This model has 2 versions which can be used. The latest version, which is the default one, corresponds to the `tapas_inter_masklm_base_reset` checkpoint of the [original Github repository](https://github.com/google-r... | [
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AiPorter/DialoGPT-small-Back_to_the_future | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
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"no_repeat_ngram_size... | 7 | null | ---
tags:
- conversational
---
# Digimon DialoGPT Model | [
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Ajay191191/autonlp-Test-530014983 | [
"pytorch",
"bert",
"text-classification",
"en",
"dataset:Ajay191191/autonlp-data-Test",
"transformers",
"autonlp",
"co2_eq_emissions"
] | text-classification | {
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],
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},
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"no_rep... | 34 | null | ---
language:
- ja
license: cc-by-sa-4.0
datasets:
- wikipedia
widget:
- text: "早稲田 大学 で 自然 言語 処理 を"
---
# nlp-waseda/gpt2-small-japanese-wikipedia
This model is Japanese GPT-2 pretrained on Japanese Wikipedia.
## Intended uses & limitations
You can use the raw model for text generation or fine-tune it to a downstr... | [
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Ajteks/Chatbot | [] | null | {
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"num_beams... | 0 | 2021-04-19T14:40:44Z | ---
language:
- en
tags:
- mental-health
license: apache-2.0
datasets:
- PubMed
---
# Psych-Search
Psych-Search is a work in progress to bring cutting edge NLP to mental health practitioners. The model detailed here serves as a foundation for traditional classification models as well as NLU models for a Psych-Search ap... | [
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Akash7897/distilbert-base-uncased-finetuned-sst2 | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:glue",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | {
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],
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},
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... | 31 | null | ---
language: en
pipeline_tag: fill-mask
license: cc-by-sa-4.0
thumbnail: https://i.ibb.co/p3kQ7Rw/Screenshot-2020-10-06-at-12-16-36-PM.png
tags:
- legal
widget:
- text: "The applicant submitted that her husband was subjected to treatment amounting to [MASK] whilst in the custody of police."
---
# LEGAL-BERT: The Mupp... | [
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Akash7897/fill_mask_model | [] | null | {
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"num_beams... | 0 | null | ---
language: en
pipeline_tag: fill-mask
license: cc-by-sa-4.0
thumbnail: https://i.ibb.co/p3kQ7Rw/Screenshot-2020-10-06-at-12-16-36-PM.png
tags:
- legal
widget:
- text: "The applicant submitted that her husband was subjected to treatment amounting to [MASK] whilst in the custody of police."
---
# LEGAL-BERT: The Mupp... | [
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Akash7897/gpt2-wikitext2 | [
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"transformers",
"generated_from_trainer",
"license:mit"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
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},
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"min_length": null,
"no_repeat_ngram_size... | 5 | null | ---
language: en
pipeline_tag: fill-mask
license: cc-by-sa-4.0
thumbnail: https://i.ibb.co/0yz81K9/sec-bert-logo.png
tags:
- finance
- financial
widget:
- text: "Total net sales [MASK] 2% or $5.4 billion during 2019 compared to 2018."
- text: "Total net sales decreased 2% or $5.4 [MASK] during 2019 compared t... | [
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Akash7897/my-newtokenizer | [] | null | {
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"num_beams... | 0 | null | ---
language: en
pipeline_tag: fill-mask
license: cc-by-sa-4.0
thumbnail: https://i.ibb.co/0yz81K9/sec-bert-logo.png
tags:
- finance
- financial
widget:
- text: "Total net sales decreased [MASK]% or $[NUM] billion during [NUM] compared to [NUM]."
- text: "Total net sales decreased [NUM]% or $[MASK] billion du... | [
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Akashpb13/Galician_xlsr | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"gl",
"dataset:mozilla-foundation/common_voice_8_0",
"transformers",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | {
"architectures": [
"Wav2Vec2ForCTC"
],
"model_type": "wav2vec2",
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},
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"min_length": null,
"no_repeat_ngram_s... | 7 | null | ---
tags:
- generated_from_keras_callback
- dpr
license: apache-2.0
model-index:
- name: dpr-ctx_encoder_bert_uncased_L-12_H-128_A-2
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this ... | [
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Akashpb13/xlsr_hungarian_new | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"hu",
"dataset:mozilla-foundation/common_voice_8_0",
"transformers",
"generated_from_trainer",
"hf-asr-leaderboard",
"model_for_talk",
"mozilla-foundation/common_voice_8_0",
"robust-speech-event",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | {
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"Wav2Vec2ForCTC"
],
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},
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"min_length": null,
"no_repeat_ngram_s... | 7 | null | ---
license: apache-2.0
tags:
- qa
datasets:
- squad_v2
- natural_questions
model-index:
- name: nlpconnect/roberta-base-squad2-nq
results:
- task:
type: question-answering
name: Question Answering
dataset:
name: squad_v2
type: squad_v2
config: squad_v2
split: validation
... | [
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Akashpb13/xlsr_kurmanji_kurdish | [
"pytorch",
"safetensors",
"wav2vec2",
"automatic-speech-recognition",
"kmr",
"ku",
"dataset:mozilla-foundation/common_voice_8_0",
"transformers",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"license:apache-... | automatic-speech-recognition | {
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"Wav2Vec2ForCTC"
],
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},
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"min_length": null,
"no_repeat_ngram_s... | 10 | null | ---
tags:
- image-to-text
- image-captioning
license: apache-2.0
widget:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/savanna.jpg
example_title: Savanna
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/football-match.jpg
example_title: Football Match
- src: https:... | [
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Aleksandar/bert-srb-base-cased-oscar | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | fill-mask | {
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"no_repeat_ngram_size... | 7 | null | ## About
`Distilgpt2` model finetuned on a dataset of inspirational/motivational quotes taken from the [Quotes-500K](https://github.com/ShivaliGoel/Quotes-500K) dataset. The model can generate inspirational quotes, many of which sound quite realistic.
## Code for Training
The code for fine-tuning the model can be foun... | [
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Aleksandar/bert-srb-ner-setimes-lr | [] | null | {
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"num_beams... | 0 | 2022-02-17T02:41:22Z | ---
license: mit
tags:
- flair
- token-classification
- sequence-tagger-model
language: "pt"
widget:
- text: "FISIOTERAPIA TRAUMATO - MANHÃ Henrique Dias, 38 anos. Exercícios metabólicos de extremidades inferiores. Realizo mobilização patelar e leve mobilização de flexão de joelho conforme liberado pelo Dr Mar... | [
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Aleksandar/bert-srb-ner-setimes | [
"pytorch",
"bert",
"token-classification",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
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"no_repeat... | 8 | 2021-04-29T10:45:50Z | # Generate News in Thai language by keywords.
MODEL_NAME = 'nonamenlp/news_gen'
TOKENIZER_NAME = "nonamenlp/news_gen"
trained_model = MT5ForConditionalGeneration.from_pretrained(MODEL_NAME, return_dict=True)
tokenizer = T5Tokenizer.from_pretrained(TOKENIZER_NAME) | [
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Aleksandar/electra-srb-ner-setimes | [
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"no_... | 6 | 2022-01-31T22:20:22Z | ---
tags:
- conversational
---
# mremoji DialoGPT Model | [
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Aleksandra/distilbert-base-uncased-finetuned-squad | [] | null | {
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"num_beams... | 0 | null | ---
tags:
- conversational
---
# 7evenpool DialoGPT Model | [
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AlekseyKulnevich/Pegasus-Summarization | [
"pytorch",
"pegasus",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"PegasusForConditionalGeneration"
],
"model_type": "pegasus",
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"n... | 7 | 2021-11-27T14:06:47Z | ---
language: en
license: apache-2.0
tags:
- generated_from_trainer
- t5-base
model-index:
- name: cover-letter-t5-base
results: []
widget:
- text: "coverletter name: Nouamane Tazi job: Machine Learning Engineer at HuggingFace background: Master's student in AI at the University of Paris Saclay experiences: I partici... | [
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AlexKay/xlm-roberta-large-qa-multilingual-finedtuned-ru | [
"pytorch",
"xlm-roberta",
"question-answering",
"en",
"ru",
"multilingual",
"arxiv:1912.09723",
"transformers",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | question-answering | {
"architectures": [
"XLMRobertaForQuestionAnswering"
],
"model_type": "xlm-roberta",
"task_specific_params": {
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... | 10,012 | null | ---
language:
- ar
license: apache-2.0
tags:
- ar
- automatic-speech-recognition
- common_voice
- generated_from_trainer
- hf-asr-leaderboard
- robust-speech-event
datasets:
- common_voice
model-index:
- name: XLS-R-300M - Arabic
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech... | [
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AlexMaclean/sentence-compression-roberta | [
"pytorch",
"roberta",
"token-classification",
"transformers",
"generated_from_trainer",
"license:mit",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"RobertaForTokenClassification"
],
"model_type": "roberta",
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"no_... | 13 | null | ---
language:
- ar
license: apache-2.0
tags:
- ar
- automatic-speech-recognition
- common_voice
- generated_from_trainer
- hf-asr-leaderboard
- robust-speech-event
datasets:
- common_voice
model-index:
- name: XLS-R-300M - Arabic
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech... | [
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AlexN/xls-r-300m-fr-0 | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_8_0",
"transformers",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"robust-speech-event",
"hf-asr-leaderboard",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | {
"architectures": [
"Wav2Vec2ForCTC"
],
"model_type": "wav2vec2",
"task_specific_params": {
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},
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"no_repeat_ngram_s... | 4 | null | ---
language:
- hu
tags:
- token-classification
license: gpl
metrics:
- F1
widget:
- text: "A jótékonysági szervezet által idézett Forbes-adatok szerint a világ tíz leggazdagabb embere: Elon Musk (Tesla, SpaceX), Jeff Bezos (Amazon, Blue Origin), Bernard Arnault és családja (LVMH, azaz Louis Vuitton és Moët Henness... | [
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AlexaRyck/KEITH | [] | null | {
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"num_beams... | 0 | null | ---
license: mit
language: en
tags:
- conversational
- npc-engine
---
# BART chatbot trained on [LIGHT](https://parl.ai/projects/light/) dataset with [Text Generative Adversarial Imitation Learning](https://arxiv.org/abs/2004.13796)
This model is intended to be used with [npc-engine](https://github.com/npc-engine/npc-... | [
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Alexander-Learn/bert-finetuned-ner-accelerate | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
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"no_repeat... | 4 | null | ---
license: mit
language: en
tags:
- text-to-speech
- npc-engine
---
# Exported [FlowtronTTS](https://arxiv.org/abs/2005.05957) with [WaveGlow](https://arxiv.org/abs/1811.00002) vocoder
This model is intended to be used with [npc-engine](https://github.com/npc-engine/npc-engine).
Fork used for exporting https://gith... | [
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Alexander-Learn/bert-finetuned-ner | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
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"no_repeat... | 8 | null | ---
license: mit
language: en
tags:
- speech-to-text
- npc-engine
---
# Exported [Nemo](https://github.com/NVIDIA/NeMo) models for Speech to Text with [OpenSLR 11](https://www.openslr.org/11/) librispeech 3-gram language model
This model is intended to be used with [npc-engine](https://github.com/npc-engine/npc-engine... | [
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Alexander-Learn/bert-finetuned-squad-accelerate | [] | null | {
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"num_beams... | 0 | null | ---
license: mit
language: en
tags:
- sentence-similarity
- npc-engine
---
# Export of [sentence-transformers/paraphrase-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/paraphrase-MiniLM-L6-v2)
This model is intended to be used with [npc-engine](https://github.com/npc-engine/npc-engine).
| [
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AlexeyYazev/my-awesome-model | [] | null | {
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"num_beams... | 0 | null | This is the BERT-Medium model from Google: https://github.com/google-research/bert#bert. A BERT model with 2 layers, 128 hidden unit size, and 2 attention heads. | [
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Alfia/anekdotes | [] | null | {
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"num_beams... | 0 | null | ---
license: mit
---
## MiniLM: 3 Layer Version
This is a 3 layer version of [microsoft/MiniLM-L12-H384-uncased](https://huggingface.co/microsoft/MiniLM-L12-H384-uncased/) by keeping only the layer [3, 7, 11]. | [
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Alireza1044/albert-base-v2-rte | [
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"text-classification",
"en",
"dataset:glue",
"transformers",
"generated_from_trainer",
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"no... | 30 | null | # MiniLMv2
This is a MiniLMv2 model from: [https://github.com/microsoft/unilm](https://github.com/microsoft/unilm/tree/master/minilm) | [
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Amrrs/indian-foods | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index",
"autotrain_compatible"
] | image-classification | {
"architectures": [
"ViTForImageClassification"
],
"model_type": "vit",
"task_specific_params": {
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},
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"no_repeat_n... | 33 | null | <!---
# ##############################################################################################
#
# Copyright (c) 2021-, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obt... | [
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Andrija/SRoBERTa-base-NER | [
"pytorch",
"roberta",
"token-classification",
"hr",
"sr",
"multilingual",
"dataset:hr500k",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"RobertaForTokenClassification"
],
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},
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"no_... | 12 | null | ---
language: zh-tw
datasets: DRCD
tasks: Question Answering
---
# BERT DRCD 384
This model is a fine-tune checkpoint of [bert-base-chinese](https://huggingface.co/bert-base-chinese), fine-tuned on DRCD dataset.
This model reaches a F1 score of 86.
This model reaches a EM score of 83.
Training Arguments:
- length:... | [
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AnonymousSub/AR_rule_based_roberta_only_classfn_epochs_1_shard_1 | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
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"no_repeat_ngram_size... | 7 | null | # BERT MCN-Model using SMM4H 2017 (subtask 3) data
The model was trained using [clagator/biobert_v1.1_pubmed_nli_sts](https://huggingface.co/clagator/biobert_v1.1_pubmed_nli_sts) as a base and the smm4h dataset from 2017 from subtask 3.
## Dataset
See [here](https://github.com/olastor/medical-concept-normalization/... | [
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license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: distilgpt2-finetuned-reddit-aita-text-gen
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment.... | [
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language: en
datasets:
- LJSpeech
- LibriTTS
tags:
- audio
- TTS
license: apache-2.0
---
# ontocord/fastspeech2-en
Modified version of the text-to-speech system [FastSpeech 2: Fast and High-Quality End-to-End Text to Speech] (https://arxiv.org/abs/2006.04558v1).
## Installation
```
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language: vi
datasets:
- common_voice
- FOSD: https://data.mendeley.com/datasets/k9sxg2twv4/4
metrics:
- wer
tags:
- language-modeling
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
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language: vi
datasets:
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metrics:
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tags:
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license: apache-2.0
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tags:
- conversational
---
# Elon Musk DialogGPT Model | [
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tags:
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widget:
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candidate_labels: playing music, playing sports
example_title: Cat & Dog
---
# Model Card: CLIP
Disclaimer: The model card is taken and modified from the official CLIP repository, it can be found [h... | [
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tags:
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widget:
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candidate_labels: playing music, playing sports
example_title: Cat & Dog
---
# Model Card: CLIP
Disclaimer: The model card is taken and modified from the official CLIP repository, it can be found ... | [
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tags:
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widget:
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candidate_labels: playing music, playing sports
example_title: Cat & Dog
---
# Model Card: CLIP
Disclaimer: The model card is taken and modified from the official CLIP repository, it can be found ... | [
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license: apache-2.0
tags:
- vision
datasets:
- imagenet-21k
---
# ImageGPT (large-sized model)
ImageGPT (iGPT) model pre-trained on ImageNet ILSVRC 2012 (14 million images, 21,843 classes) at resolution 32x32. It was introduced in the paper [Generative Pretraining from Pixels](https://cdn.openai.com/papers/Gener... | [
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license: apache-2.0
tags:
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datasets:
- imagenet-21k
---
# ImageGPT (medium-sized model)
ImageGPT (iGPT) model pre-trained on ImageNet ILSVRC 2012 (14 million images, 21,843 classes) at resolution 32x32. It was introduced in the paper [Generative Pretraining from Pixels](https://cdn.openai.com/papers/Gene... | [
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license: apache-2.0
tags:
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datasets:
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---
# ImageGPT (small-sized model)
ImageGPT (iGPT) model pre-trained on ImageNet ILSVRC 2012 (14 million images, 21,843 classes) at resolution 32x32. It was introduced in the paper [Generative Pretraining from Pixels](https://cdn.openai.com/papers/Gener... | [
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license: mit
tags:
- nowcasting
- forecasting
- timeseries
- remote-sensing
- gan
---
# DGMR
## Model description
[More information needed]
## Intended uses & limitations
[More information needed]
## How to use
[More information needed]
## Limitations and bias
[More information needed]
## Training data
[... | [
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language: multilingual
tags:
- Extract Names
license: apache-2.0
---
## Extract names in any language.
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# MyModelName
Borges02
## Model description
You can generate new short stories from Jorge Luis Borges.
## Intended uses & limitations
#### How to use
```python
# You can include sample code which will be formatted
```
#### Limitations and bias
Provide examples of latent issues and potential remediations.
## T... | [
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language: ru
---
BART model fine-tuned to aggregate crowd-sourced transcriptions.
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"no_repeat_ngram_s... | 7 | null | Text simplification model for Russian. Fine-tuned ruGPT3-large
https://github.com/orzhan/rusimscore
---
language: ru
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"no_repeat_ngram_s... | 6 | null | T5-small model fine-tuned for extractive summarization on long documents.
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"no_rep... | 30 | null | This is a t5-base model trained on the multi_news dataset for abstraction summarization | [
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AnonymousSub/bert_hier_diff_equal_wts_epochs_1_shard_10 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
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"no_repeat_ngram_size": nul... | 1 | null | ---
tags:
- text-to-image
library_name: generic
---
# Image generation using pretrained BigGAN
## Warning: This only works for ImageNet inputs.
List of possible inputs: https://gist.github.com/yrevar/942d3a0ac09ec9e5eb3a
GitHub repository: https://github.com/huggingface/pytorch-pretrained-BigGAN
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AnonymousSub/bert_mean_diff_epochs_1_shard_1 | [
"pytorch",
"bert",
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"transformers"
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"no_repeat_ngram_size": nul... | 6 | null | ---
tags:
- audio
- ConvTasNet
- audio-to-audio
datasets:
- Libri1Mix
- enh_single
license: cc-by-sa-4.0
library_tag: generic
---
## Clone from Asteroid model `JorisCos/ConvTasNet_Libri1Mix_enhsignle_16k`
Description:
This model was trained by Joris Cosentino using the librimix recipe in [Asteroid](https://github.co... | [
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AnonymousSub/bert_snips | [
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tags:
- adapter-transformers
---
# Adapter transformers | [
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AnonymousSub/bert_triplet_epochs_1_shard_1 | [
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"no_repeat_ngram_size": nul... | 2 | null | ---
benchmark: superb
library_name: superb
language: en
datasets:
- librispeech_asr
tags:
- audio
- automatic-speech-recognition
- superb
license: apache-2.0
widget:
- example_title: Librispeech sample 1
src: https://cdn-media.huggingface.co/speech_samples/sample1.flac
- example_title: Librispeech sample 2
src: htt... | [
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AnonymousSub/bert_triplet_epochs_1_shard_10 | [
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"no_repeat_ngram_size": nul... | 1 | null | ---
tags:
- audio-to-audio
library_name: generic
---
# Audio to Audio repository template
This is a template repository for Audio to Audio to support generic inference with Hugging Face Hub generic Inference API. Examples of Audio to Audio are Source Separation and Speech Enhancement. There are two required steps:
1... | [
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AnonymousSub/cline-emanuals-s10-SR | [] | null | {
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"num_beams... | 0 | null | ---
tags:
- allennlp
- question-answering
---
# TODO: Fill this model card
| [
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AnonymousSub/cline-emanuals-techqa | [
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"roberta",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | {
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"no_re... | 4 | null | ---
tags:
- sentence-transformers
- feature-extraction
---
# TODO: Name of Model
TODO: Description
## Model Description
TODO: Add relevant content
(0) Base Transformer Type: DistilBertModel
(1) Pooling mean
(2) Dense 768x512
## Usage (Sentence-Transformers)
Using this model becomes more convenient when you hav... | [
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AnonymousSub/consert-s10-SR | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
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"no_rep... | 28 | 2021-08-17T08:22:19Z | ---
library_name: generic
language:
- en
pipeline_tag: text-to-image
---
## Fork of DALL·E mini - Generate images from text
For the original repo, head to https://huggingface.co/flax-community/dalle-mini | [
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AnonymousSub/dummy_2 | [
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"no_rep... | 39 | null | ---
tags:
- spacy
- token-classification
language:
- en
model-index:
- name: fashion_brands_patterns
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.0
- name: NER Recall
type: recall
value: 0.0
- name: ... | [
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AnonymousSub/dummy_2_parent | [
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tags:
- image-classification
library_name: generic
---
# Dog vs Cat Image Classification with FastAI CNN
Training is based in FastAI [Quick Start](https://docs.fast.ai/quick_start.html). Example training
## Training
The model was trained as follows
```python
path = untar_data(URLs.PETS)/'images'
def is_cat(x... | [
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AnonymousSub/rule_based_bert_hier_diff_equal_wts_epochs_1_shard_1 | [
"pytorch",
"bert",
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"transformers"
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"no_repeat_ngram_size": nul... | 8 | 2021-05-18T07:19:49Z | ---
tags:
- translation
widget:
- text: "I have a problem with my iphone that needs to be resolved asap!!"
- max_length: 1
license: apache-2.0
---
# Fastspeech english model | [
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AnonymousSub/rule_based_bert_quadruplet_epochs_1_shard_1 | [
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"no_repeat_ngram_size": nul... | 8 | null | ---
tags:
- text-classification
library_name: fasttext
widget:
- text: "apple"
example_title: "apple"
- text: "cat"
example_title: "cat"
- text: "sunny"
example_title: "sunny"
- text: "water"
example_title: "water"
---
# Fasttext nearest neighbors | [
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