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 |
|---|---|---|---|---|---|---|---|
Aleksandar1932/gpt2-soul | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 10 | null | ---
tags:
- image-classification
- timm
library_tag: timm
license: apache-2.0
---
# Model card for resnet50d.a2_in1k
A ResNet-D image classification model.
This model features:
* ReLU activations
* 3-layer stem of 3x3 convolutions with pooling
* 2x2 average pool + 1x1 convolution shortcut downsample
Trained on Im... | [
-0.0038274284452199936,
-0.014774550683796406,
-0.008695564232766628,
0.0261094868183136,
0.03485356643795967,
-0.008448869921267033,
-0.004970121197402477,
-0.009205194190144539,
-0.012037735432386398,
0.05594737082719803,
0.020165618509054184,
-0.002210300648584962,
-0.01903425343334675,
... |
Alexander-Learn/bert-finetuned-squad | [
"pytorch",
"tensorboard",
"bert",
"question-answering",
"transformers",
"autotrain_compatible"
] | 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... | 7 | null | ---
tags:
- image-classification
- timm
library_tag: timm
license: apache-2.0
---
# Model card for resnet152.gluon_in1k
A ResNet-B image classification model.
This model features:
* ReLU activations
* single layer 7x7 convolution with pooling
* 1x1 convolution shortcut downsample
Trained on ImageNet-1k in Apache ... | [
-0.011523278430104256,
-0.023556267842650414,
-0.0024206088855862617,
0.025767134502530098,
0.031211499124765396,
0.0016719403211027384,
-0.0005405291449278593,
-0.002692390466108918,
-0.004692309070378542,
0.04549403861165047,
0.027124229818582535,
0.002522674622014165,
-0.00489271013066172... |
AlexeyIgnatov/albert-xlarge-v2-squad-v2 | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
tags:
- image-classification
- timm
library_tag: timm
license: bsd-3-clause
---
# Model card for resnet152.tv2_in1k
A ResNet-B image classification model.
This model features:
* ReLU activations
* single layer 7x7 convolution with pooling
* 1x1 convolution shortcut downsample
Trained on ImageNet-1k in torchvi... | [
-0.008356445468962193,
-0.02674497291445732,
-0.0007578846998512745,
0.0332232266664505,
0.03615676984190941,
-0.004184978548437357,
-0.010722456499934196,
-0.007609866093844175,
-0.007764971815049648,
0.04784911498427391,
0.02141757681965828,
0.004084908869117498,
-0.01166067086160183,
0.... |
Alfia/anekdotes | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
tags:
- image-classification
- timm
library_tag: timm
license: apache-2.0
---
# Model card for resnet152c.gluon_in1k
A ResNet-C image classification model.
This model features:
* ReLU activations
* 3-layer stem of 3x3 convolutions with pooling
* 1x1 convolution shortcut downsample
Trained on ImageNet-1k in Ap... | [
-0.011609090492129326,
-0.02482413314282894,
-0.003097470849752426,
0.0253012515604496,
0.02876218594610691,
0.00007149312295950949,
-0.00794824305921793,
-0.005369117017835379,
-0.006393583957105875,
0.04741440713405609,
0.0265284925699234,
0.002903308952227235,
-0.009548882953822613,
0.0... |
AlgoveraAI/dcgan | [
"pytorch",
"transformers"
] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 12 | null | ---
tags:
- image-classification
- timm
library_tag: timm
license: apache-2.0
---
# Model card for resnet152d.gluon_in1k
A ResNet-D image classification model.
This model features:
* ReLU activations
* 3-layer stem of 3x3 convolutions with pooling
* 2x2 average pool + 1x1 convolution shortcut downsample
Trained o... | [
-0.013194320723414421,
-0.02391677163541317,
-0.004230710677802563,
0.02746129222214222,
0.030768755823373795,
0.0006634003948420286,
-0.005349432118237019,
-0.007476221304386854,
-0.007383900694549084,
0.04878360033035278,
0.0246965941041708,
0.0028171134181320667,
-0.007345438934862614,
... |
Alireza1044/albert-base-v2-mnli | [
"pytorch",
"albert",
"text-classification",
"en",
"dataset:glue",
"transformers",
"generated_from_trainer",
"license:apache-2.0"
] | text-classification | {
"architectures": [
"AlbertForSequenceClassification"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no... | 235 | null | ---
tags:
- image-classification
- timm
library_tag: timm
license: apache-2.0
---
# Model card for resnet200d.ra2_in1k
A ResNet-D image classification model.
This model features:
* ReLU activations
* 3-layer stem of 3x3 convolutions with pooling
* 2x2 average pool + 1x1 convolution shortcut downsample
Trained on ... | [
-0.0007776356651447713,
-0.015186809003353119,
-0.0067530302330851555,
0.01909451372921467,
0.04210348054766655,
0.0032257926650345325,
0.001977815991267562,
-0.007881419733166695,
-0.022488901391625404,
0.06534584611654282,
0.02480822429060936,
-0.0010019182227551937,
-0.022253571078181267,... |
Allybaby21/Allysai | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
tags:
- image-classification
- timm
library_tag: timm
license: apache-2.0
---
# Model card for resnetrs152.tf_in1k
A ResNetRS-B image classification model.
This model features:
* ReLU activations
* single layer 7x7 convolution with pooling
* 1x1 convolution shortcut downsample
Trained on ImageNet-1k by paper ... | [
-0.007242769934237003,
-0.024326544255018234,
-0.006688979919999838,
0.025842325761914253,
0.02459903061389923,
0.004199100658297539,
-0.011364673264324665,
-0.004487085156142712,
-0.010285315103828907,
0.04790361970663071,
0.0029923315159976482,
-0.004401941318064928,
0.004722742363810539,
... |
Aloka/mbart50-ft-si-en | [
"pytorch",
"tensorboard",
"mbart",
"text2text-generation",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"MBartForConditionalGeneration"
],
"model_type": "mbart",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 4 | null | ---
license: openrail
datasets:
- Ali-fb/martin_valen_dataset
language:
- en
metrics:
- accuracy
library_name: diffusers
pipeline_tag: text-to-image
tags:
- art
--- | [
-0.006674397736787796,
-0.0015120909083634615,
-0.004545502830296755,
0.01712653413414955,
0.0737098827958107,
0.012237965129315853,
-0.01438891887664795,
0.013042405247688293,
-0.028541844338178635,
0.05655985698103905,
0.016227344051003456,
0.016301237046718597,
0.016629483550786972,
0.0... |
Alvenir/wav2vec2-base-da | [
"pytorch",
"wav2vec2",
"pretraining",
"da",
"transformers",
"speech",
"license:apache-2.0"
] | null | {
"architectures": [
"Wav2Vec2ForPreTraining"
],
"model_type": "wav2vec2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 62 | null | ---
tags:
- image-classification
- timm
library_tag: timm
license: apache-2.0
---
# Model card for resnetrs200.tf_in1k
A ResNetRS-B image classification model.
This model features:
* ReLU activations
* single layer 7x7 convolution with pooling
* 1x1 convolution shortcut downsample
Trained on ImageNet-1k by paper ... | [
-0.007185241673141718,
-0.024314388632774353,
-0.007252219598740339,
0.025951631367206573,
0.023742297664284706,
0.00452090660110116,
-0.010267000645399094,
-0.0041419630870223045,
-0.01013968139886856,
0.04843749850988388,
0.002410950604826212,
-0.004549580160528421,
0.0069724335335195065,
... |
Amalq/distilroberta-base-finetuned-MentalHealth | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
tags:
- image-classification
- timm
library_tag: timm
license: apache-2.0
---
# Model card for resnetrs270.tf_in1k
A ResNetRS-B image classification model.
This model features:
* ReLU activations
* single layer 7x7 convolution with pooling
* 1x1 convolution shortcut downsample
Trained on ImageNet-1k by paper ... | [
-0.0070699467323720455,
-0.02442312426865101,
-0.007528173271566629,
0.025614319369196892,
0.025259317830204964,
0.0055158305913209915,
-0.010639538988471031,
-0.004790879786014557,
-0.010810083709657192,
0.047501735389232635,
0.002565247705206275,
-0.002647773362696171,
0.006235228851437569... |
Amalq/roberta-base-finetuned-schizophreniaReddit2 | [
"pytorch",
"tensorboard",
"roberta",
"fill-mask",
"transformers",
"generated_from_trainer",
"license:mit",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngra... | 5 | null | ---
tags:
- image-classification
- timm
library_tag: timm
license: apache-2.0
---
# Model card for resnetrs350.tf_in1k
A ResNetRS-B image classification model.
This model features:
* ReLU activations
* single layer 7x7 convolution with pooling
* 1x1 convolution shortcut downsample
Trained on ImageNet-1k by paper ... | [
-0.0065045468509197235,
-0.02294572815299034,
-0.007601782213896513,
0.024918165057897568,
0.02460937388241291,
0.005180457606911659,
-0.011088904924690723,
-0.005823802202939987,
-0.010463613085448742,
0.04782816395163536,
0.003205630462616682,
-0.00486887339502573,
0.005687348544597626,
... |
AmanPriyanshu/DistilBert-Sentiment-Analysis | [
"tf",
"distilbert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | 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... | 7 | null | ---
tags:
- image-classification
- timm
library_tag: timm
license: apache-2.0
---
# Model card for resnetrs420.tf_in1k
A ResNetRS-B image classification model.
This model features:
* ReLU activations
* single layer 7x7 convolution with pooling
* 1x1 convolution shortcut downsample
Trained on ImageNet-1k by paper ... | [
-0.009164432063698769,
-0.022825084626674652,
-0.007009152788668871,
0.03044789470732212,
0.026511160656809807,
0.007050170097500086,
-0.013348751701414585,
-0.0021356730721890926,
-0.010122212581336498,
0.04654732719063759,
0.0018607336096465588,
-0.0034552847500890493,
0.006861225701868534... |
Amba/wav2vec2-large-xls-r-300m-tr-colab | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
tags:
- image-classification
- timm
library_tag: timm
license: apache-2.0
---
# Model card for resnext50_32x4d.a1_in1k
A ResNeXt-B image classification model.
This model features:
* ReLU activations
* single layer 7x7 convolution with pooling
* 1x1 convolution shortcut downsample
* grouped 3x3 bottleneck conv... | [
-0.0061247763223946095,
-0.016825169324874878,
-0.005297818686813116,
0.028846528381109238,
0.029102275148034096,
0.0003667093114927411,
-0.0034919693134725094,
-0.00817058514803648,
-0.017233720049262047,
0.050562284886837006,
0.023276887834072113,
-0.0004464484809432179,
-0.015729684382677... |
aisoftware/Loquela | [
"onnx"
] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
tags:
- image-classification
- timm
library_tag: timm
license: apache-2.0
---
# Model card for resnext50_32x4d.a2_in1k
A ResNeXt-B image classification model.
This model features:
* ReLU activations
* single layer 7x7 convolution with pooling
* 1x1 convolution shortcut downsample
* grouped 3x3 bottleneck conv... | [
-0.006799723487347364,
-0.017365535721182823,
-0.005159755237400532,
0.029390357434749603,
0.02888350374996662,
0.00011769148841267452,
-0.0035745245404541492,
-0.008015086874365807,
-0.017789969220757484,
0.050802335143089294,
0.02269933372735977,
0.0017256292048841715,
-0.01738770492374897... |
Amro-Kamal/gpt | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
tags:
- image-classification
- timm
library_tag: timm
license: bsd-3-clause
---
# Model card for resnext50_32x4d.tv_in1k
A ResNeXt-B image classification model.
This model features:
* ReLU activations
* single layer 7x7 convolution with pooling
* 1x1 convolution shortcut downsample
* grouped 3x3 bottleneck co... | [
-0.011717558838427067,
-0.02647537924349308,
0.0029607268515974283,
0.02995903789997101,
0.028133396059274673,
0.001351795857772231,
-0.016861723735928535,
-0.007109247148036957,
-0.0175960510969162,
0.04685642570257187,
0.023914676159620285,
0.0032298192381858826,
-0.013000259175896645,
0... |
Amrrs/indian-foods | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index",
"autotrain_compatible"
] | image-classification | {
"architectures": [
"ViTForImageClassification"
],
"model_type": "vit",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_n... | 33 | null | ---
tags:
- image-classification
- timm
library_tag: timm
license: apache-2.0
---
# Model card for resnext50d_32x4d.bt_in1k
A ResNeXt-D image classification model.
This model features:
* ReLU activations
* 3-layer stem of 3x3 convolutions with pooling
* 2x2 average pool + 1x1 convolution shortcut downsample
* gro... | [
-0.014396453276276588,
-0.018154533579945564,
-0.0035681615117937326,
0.029403438791632652,
0.031300876289606094,
0.004977649077773094,
-0.008197668939828873,
-0.006573570426553488,
-0.016256233677268028,
0.05013081058859825,
0.028288135305047035,
0.005029211286455393,
-0.022738205268979073,... |
Andranik/TestPytorchClassification | [
"pytorch",
"distilbert",
"text-classification",
"transformers"
] | 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,
... | 36 | null | ---
tags:
- image-classification
- timm
library_tag: timm
license: bsd-3-clause
---
# Model card for resnext101_32x8d.tv_in1k
A ResNeXt-B image classification model.
This model features:
* ReLU activations
* single layer 7x7 convolution with pooling
* 1x1 convolution shortcut downsample
* grouped 3x3 bottleneck c... | [
-0.01020700391381979,
-0.029448192566633224,
0.003247150219976902,
0.029916265979409218,
0.027645321562886238,
0.0012301778187975287,
-0.01497361809015274,
-0.006635550409555435,
-0.017745718359947205,
0.04914383962750435,
0.022107815369963646,
0.0026171847712248564,
-0.011175652965903282,
... |
Andranik/TestQA2 | [
"pytorch",
"electra",
"question-answering",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"ElectraForQuestionAnswering"
],
"model_type": "electra",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 8 | null | ---
tags:
- image-classification
- timm
library_tag: timm
license: cc-by-nc-4.0
---
# Model card for resnext101_32x16d.fb_ssl_yfcc100m_ft_in1k
A ResNeXt-B image classification model.
This model features:
* ReLU activations
* single layer 7x7 convolution with pooling
* 1x1 convolution shortcut downsample
* grouped... | [
-0.013306807726621628,
-0.02648254670202732,
-0.003629119135439396,
0.02425331622362137,
0.02356414869427681,
0.014470758847892284,
-0.013501814566552639,
-0.00947368610650301,
-0.013539624400436878,
0.048015594482421875,
0.026601368561387062,
-0.002855362370610237,
-0.0021011175122112036,
... |
AndreLiu1225/t5-news | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"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... | 18 | null | ---
tags:
- CartPole-v1
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: Reinforce-v1
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: CartPole-v1
type: CartPole-v1
metrics:
- type: mean_rew... | [
-0.029807506129145622,
0.019034026190638542,
0.005308631341904402,
0.009276989847421646,
0.04453130066394806,
-0.01890845224261284,
-0.02233903482556343,
-0.014218106865882874,
-0.029247649013996124,
0.08463586121797562,
0.018464678898453712,
-0.00794339831918478,
0.017813237383961678,
0.0... |
Andres2015/HiggingFaceTest | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
datasets:
- sroie
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: perioli_vgm_v4.1
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: sroie
type: sroie
config: discharg... | [
-0.010949148796498775,
-0.006101639475673437,
0.0013131438754498959,
0.015525034628808498,
0.043303750455379486,
-0.006359848193824291,
-0.009058641269803047,
-0.008758576586842537,
-0.0260151494294405,
0.056292202323675156,
0.04898080974817276,
-0.03558247908949852,
0.011021368205547333,
... |
AndrewMcDowell/wav2vec2-xls-r-1B-german | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"de",
"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": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_s... | 8 | null | ---
tags:
- image-classification
- timm
library_tag: timm
license: cc-by-nc-4.0
---
# Model card for resnext101_32x16d.fb_wsl_ig1b_ft_in1k
A ResNeXt-B image classification model.
This model features:
* ReLU activations
* single layer 7x7 convolution with pooling
* 1x1 convolution shortcut downsample
* grouped 3x3... | [
-0.017383553087711334,
-0.03306260704994202,
-0.007774989120662212,
0.021936487406492233,
0.031271956861019135,
0.01616653800010681,
-0.02913365513086319,
0.006240935996174812,
-0.0049486528150737286,
0.05786165967583656,
0.04228775203227997,
-0.0072885602712631226,
-0.018338317051529884,
... |
AndrewMcDowell/wav2vec2-xls-r-1b-arabic | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ar",
"dataset:common_voice",
"transformers",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"license:apache-2.0"
] | automatic-speech-recognition | {
"architectures": [
"Wav2Vec2ForCTC"
],
"model_type": "wav2vec2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_s... | 7 | null | ---
library_name: ml-agents
tags:
- Pyramids
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-Pyramids
---
# **ppo** Agent playing **Pyramids**
This is a trained model of a **ppo** agent playing **Pyramids** using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
... | [
-0.05095725879073143,
0.0011021087411791086,
-0.004696485586464405,
0.04977581650018692,
0.026564717292785645,
0.03175783157348633,
-0.011336738243699074,
-0.02227160893380642,
-0.000704633304849267,
0.051334451884031296,
0.024760572239756584,
-0.01188243180513382,
0.007245173212140799,
0.... |
AndrewMcDowell/wav2vec2-xls-r-300m-arabic | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ar",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"generated_from_trainer",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_7_0",
"robust-speech-event",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | {
"architectures": [
"Wav2Vec2ForCTC"
],
"model_type": "wav2vec2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_s... | 4 | 2023-04-05T19:18:34Z | ---
tags:
- image-classification
- timm
library_tag: timm
license: cc-by-nc-4.0
---
# Model card for resnext101_32x32d.fb_wsl_ig1b_ft_in1k
A ResNeXt-B image classification model.
This model features:
* ReLU activations
* single layer 7x7 convolution with pooling
* 1x1 convolution shortcut downsample
* grouped 3x3... | [
-0.017627211287617683,
-0.03291767090559006,
-0.00747928861528635,
0.02163621038198471,
0.031084125861525536,
0.01574028842151165,
-0.029423650354146957,
0.005964749958366156,
-0.005310073960572481,
0.05751529335975647,
0.04240794479846954,
-0.00718336645513773,
-0.01853499747812748,
0.019... |
Andrija/SRoBERTa-F | [
"pytorch",
"tensorboard",
"roberta",
"fill-mask",
"hr",
"sr",
"multilingual",
"dataset:oscar",
"dataset:srwac",
"dataset:leipzig",
"dataset:cc100",
"dataset:hrwac",
"transformers",
"masked-lm",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngra... | 59 | null | ---
license: openrail
datasets:
- alan-txi/dnd-monsters
language:
- en
tags:
- art
--- | [
-0.024315107613801956,
-0.0271855928003788,
0.005883981008082628,
0.01574014499783516,
0.07682494819164276,
0.016748761758208275,
-0.01008209865540266,
-0.0065863411873579025,
-0.0034382750745862722,
0.041737332940101624,
0.03207322582602501,
0.01581861451268196,
0.015184170566499233,
0.03... |
Andrija/SRoBERTa-L | [
"pytorch",
"roberta",
"fill-mask",
"hr",
"sr",
"multilingual",
"dataset:oscar",
"dataset:srwac",
"dataset:leipzig",
"transformers",
"masked-lm",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngra... | 58 | null | ---
tags:
- image-classification
- timm
library_tag: timm
license: apache-2.0
---
# Model card for seresnet50.a1_in1k
A SE-ResNet-B image classification model with Squeeze-and-Excitation channel attention.
This model features:
* ReLU activations
* single layer 7x7 convolution with pooling
* 1x1 convolution shortcu... | [
-0.007251562550663948,
-0.010488707572221756,
-0.005161706358194351,
0.029618609696626663,
0.03418952599167824,
-0.007308270316570997,
-0.002841582987457514,
-0.013403724879026413,
-0.009050533175468445,
0.061737705022096634,
0.02595510520040989,
0.0018549351952970028,
-0.01855454407632351,
... |
Andrija/SRoBERTa-NER | [
"pytorch",
"roberta",
"token-classification",
"hr",
"sr",
"multilingual",
"dataset:hr500k",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"RobertaForTokenClassification"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_... | 7 | null | ---
tags:
- image-classification
- timm
library_tag: timm
license: apache-2.0
---
# Model card for seresnet50.a2_in1k
A SE-ResNet-B image classification model with Squeeze-and-Excitation channel attention.
This model features:
* ReLU activations
* single layer 7x7 convolution with pooling
* 1x1 convolution shortcu... | [
-0.008057042956352234,
-0.01143972110003233,
-0.004585057031363249,
0.030029499903321266,
0.03402738645672798,
-0.007345673628151417,
-0.002886394038796425,
-0.013205206952989101,
-0.00937960296869278,
0.0614628791809082,
0.025303268805146217,
0.004527308512479067,
-0.0200229212641716,
0.0... |
Andrija/SRoBERTa-NLP | [
"pytorch",
"roberta",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"RobertaForTokenClassification"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_... | 7 | null | ---
title: GenerAd AI
emoji: 🔥
colorFrom: yellow
colorTo: red
sdk: gradio
sdk_version: 3.24.1
app_file: app.py
pinned: false
license: bigscience-openrail-m
--- | [
-0.040985096246004105,
-0.0012351889163255692,
-0.014515938237309456,
0.044980328530073166,
0.09044588357210159,
0.02700696513056755,
-0.014310594648122787,
-0.021694805473089218,
-0.0239630788564682,
0.030787138268351555,
0.03539260849356651,
0.004549889825284481,
0.015028156340122223,
0.... |
Andrija/SRoBERTa-XL-NER | [
"pytorch",
"roberta",
"token-classification",
"hr",
"sr",
"multilingual",
"dataset:hr500k",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"RobertaForTokenClassification"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_... | 6 | null | ---
tags:
- image-classification
- timm
library_tag: timm
license: apache-2.0
---
# Model card for seresnet50.a3_in1k
A SE-ResNet-B image classification model with Squeeze-and-Excitation channel attention.
This model features:
* ReLU activations
* single layer 7x7 convolution with pooling
* 1x1 convolution shortcu... | [
-0.00906533282250166,
-0.011303417384624481,
-0.007214441429823637,
0.0284712053835392,
0.03503238782286644,
-0.0067726136185228825,
-0.0042374529875814915,
-0.014291737228631973,
-0.009275530464947224,
0.06358607858419418,
0.025928309187293053,
0.0017552407225593925,
-0.020188843831419945,
... |
Andrija/SRoBERTa-XL | [
"pytorch",
"roberta",
"fill-mask",
"hr",
"sr",
"multilingual",
"dataset:oscar",
"dataset:srwac",
"dataset:leipzig",
"dataset:cc100",
"dataset:hrwac",
"transformers",
"masked-lm",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngra... | 54 | null | ---
tags:
- image-classification
- timm
library_tag: timm
license: apache-2.0
---
# Model card for seresnet50.ra2_in1k
A SE-ResNet-B image classification model with Squeeze-and-Excitation channel attention.
This model features:
* ReLU activations
* single layer 7x7 convolution with pooling
* 1x1 convolution shortc... | [
-0.011652393266558647,
-0.0021690288558602333,
0.002722534816712141,
0.021399158984422684,
0.03778914362192154,
0.004783810116350651,
-0.0030869715847074986,
-0.016306806355714798,
-0.01824648678302765,
0.06781946122646332,
0.026863358914852142,
0.0010430647525936365,
-0.013992772437632084,
... |
Andrija/SRoBERTa-base-NER | [
"pytorch",
"roberta",
"token-classification",
"hr",
"sr",
"multilingual",
"dataset:hr500k",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"RobertaForTokenClassification"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_... | 12 | null | ---
tags:
- image-classification
- timm
library_tag: timm
license: apache-2.0
---
# Model card for seresnet152d.ra2_in1k
A SE-ResNet-D image classification model with Squeeze-and-Excitation channel attention.
This model features:
* ReLU activations
* 3-layer stem of 3x3 convolutions with pooling
* 2x2 average pool... | [
-0.006638918537646532,
-0.00416244100779295,
-0.0024878086987882853,
0.017727145925164223,
0.04837368056178093,
0.0057464661076664925,
-0.0004366744833532721,
-0.02341010794043541,
-0.02273533120751381,
0.07296400517225266,
0.031236940994858742,
-0.0007885178201831877,
-0.02016107365489006,
... |
Andrija/SRoBERTa-base | [
"pytorch",
"roberta",
"fill-mask",
"hr",
"sr",
"multilingual",
"dataset:oscar",
"dataset:leipzig",
"transformers",
"masked-lm",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngra... | 80 | null | ---
license: openrail
datasets:
- tthoraldson/OasisLyrics
language:
- en
library_name: transformers
pipeline_tag: text-generation
--- | [
-0.03506655991077423,
-0.005657339468598366,
-0.017094062641263008,
0.017406411468982697,
0.06638923287391663,
0.02601279877126217,
-0.012571096420288086,
0.01639169454574585,
-0.03776167705655098,
0.058528486639261246,
0.0404132679104805,
0.029461652040481567,
-0.00002060951737803407,
0.0... |
Andrija/SRoBERTaFastBPE-2 | [
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngra... | 7 | null | ---
tags:
- image-classification
- timm
library_tag: timm
license: apache-2.0
---
# Model card for seresnext26d_32x4d.bt_in1k
A SE-ResNeXt-D image classification model with Squeeze-and-Excitation channel attention.
This model features:
* ReLU activations
* 3-layer stem of 3x3 convolutions with pooling
* 2x2 averag... | [
-0.01948048546910286,
-0.013020629994571209,
0.0034050242975354195,
0.02440844289958477,
0.04225693270564079,
0.005396565888077021,
-0.01620486192405224,
-0.0174567848443985,
-0.013444775715470314,
0.06449276208877563,
0.03320099040865898,
0.008628033101558685,
-0.020552266389131546,
0.046... |
Andrija/SRoBERTaFastBPE | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
tags:
- image-classification
- timm
library_tag: timm
license: apache-2.0
---
# Model card for seresnext26t_32x4d.bt_in1k
A SE-ResNeXt-T image classification model with Squeeze-and-Excitation channel attention.
This model features:
* ReLU activations
* tiered 3-layer stem of 3x3 convolutions with pooling
* 2x2... | [
-0.019296688959002495,
-0.012079425156116486,
0.0038415982853621244,
0.026770442724227905,
0.041858553886413574,
0.0062637003138661385,
-0.018107768148183823,
-0.013177953660488129,
-0.012886960990726948,
0.06041252240538597,
0.026369763538241386,
0.0075002387166023254,
-0.02082786336541176,... |
Andry/1111 | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
tags:
- image-classification
- timm
library_tag: timm
license: apache-2.0
---
# Model card for seresnext50_32x4d.gluon_in1k
A SE-ResNeXt-B image classification model with Squeeze-and-Excitation channel attention.
This model features:
* ReLU activations
* single layer 7x7 convolution with pooling
* 1x1 convolut... | [
-0.02113070897758007,
-0.018478678539395332,
0.0035521972458809614,
0.02837785892188549,
0.028901956975460052,
0.006113406270742416,
-0.009089740924537182,
-0.016363712027668953,
-0.012598454020917416,
0.052125975489616394,
0.03054438903927803,
0.012015089392662048,
-0.009677472524344921,
... |
Ann2020/rubert-base-cased-sentence-finetuned-ner | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
tags:
- image-classification
- timm
library_tag: timm
license: apache-2.0
---
# Model card for seresnextaa101d_32x8d.sw_in12k
A SE-ResNeXt-D (Rectangle-2 Anti-Aliasing) image classification model with Squeeze-and-Excitation channel attention.
This model features:
* ReLU activations
* 3-layer stem of 3x3 convolu... | [
-0.03095976822078228,
-0.01057889498770237,
-0.0008702863706275821,
0.019296951591968536,
0.035985156893730164,
0.01263020932674408,
-0.015015640296041965,
-0.023072103038430214,
-0.013251785188913345,
0.06834746152162552,
0.02307802625000477,
-0.0007744221366010606,
-0.013520406559109688,
... |
AnonymousSub/AR_rule_based_roberta_only_classfn_twostage_epochs_1_shard_10 | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 6 | null | ---
tags:
- Taxi-v3
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: Taxi-v3-model
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Taxi-v3
type: Taxi-v3
metrics:
- type: mean_reward
value: 7.56 +/- ... | [
-0.020374346524477005,
-0.01650973968207836,
-0.01039169728755951,
0.029254430904984474,
0.04783554747700691,
-0.003741761203855276,
-0.016398290172219276,
0.008288553915917873,
-0.03378908336162567,
0.05336793139576912,
0.016592860221862793,
-0.004124853760004044,
0.01040103379637003,
0.0... |
AnonymousSub/AR_rule_based_roberta_twostagequadruplet_hier_epochs_1_shard_1 | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 5 | null | ---
duplicated_from: Michau/t5-base-en-generate-headline
---
## About the model
The model has been trained on a collection of 500k articles with headings. Its purpose is to create a one-line heading suitable for the given article.
Sample code with a WikiNews article:
```python
import torch
from transformers import T... | [
-0.03406336158514023,
-0.03891001641750336,
-0.013103133998811245,
0.04726070910692215,
0.031046485528349876,
0.03897085040807724,
0.005939459428191185,
-0.02460123598575592,
-0.03831164538860321,
0.02880173549056053,
0.01879720389842987,
0.03496462106704712,
0.012139780446887016,
0.034831... |
AnonymousSub/AR_rule_based_roberta_twostagequadruplet_hier_epochs_1_shard_10 | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 4 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- banking77
metrics:
- f1
model-index:
- name: bert-base-banking77-pt2
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: banking77
type: banking77
config: default
split: test
... | [
-0.03276168182492256,
0.008505160920321941,
-0.005161562468856573,
0.023537948727607727,
0.022271418944001198,
0.02988888882100582,
-0.006314168684184551,
-0.016177471727132797,
-0.029958104714751244,
0.04670845344662666,
0.023822462186217308,
-0.020771948620676994,
-0.003349949372932315,
... |
AnonymousSub/SR_EManuals-RoBERTa | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 1 | null | ---
language: en
license: apache-2.0
pipeline_tag: summarization
---
# Model Card
This model is identical to [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384), except the `generation_config.json` has been updated from:
```json
{
"_from_model_config": true,
"bos_token_id": 0,
"decoder_star... | [
-0.022780919447541237,
-0.009034082293510437,
-0.004685442894697189,
0.008899681270122528,
0.029244134202599525,
-0.007839778438210487,
-0.018149351701140404,
-0.0004219988186378032,
-0.04741901531815529,
0.06193748116493225,
0.0567508190870285,
-0.02405822090804577,
0.019396699965000153,
... |
AnonymousSub/SR_rule_based_roberta_hier_triplet_epochs_1_shard_10 | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 6 | null | ---
license: openrail
library_name: transformers
pipeline_tag: text-generation
--- | [
-0.03319612517952919,
0.0027060185093432665,
-0.015235588885843754,
0.006601655390113592,
0.06587819755077362,
0.03151718154549599,
-0.013731964863836765,
0.014463216066360474,
-0.03812786936759949,
0.05044543370604515,
0.03358057886362076,
0.014577995054423809,
0.0021127574145793915,
0.04... |
AnonymousSub/SR_rule_based_roberta_only_classfn_twostage_epochs_1_shard_10 | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 4 | null | ---
datasets:
- tatsu-lab/alpaca
language:
- en
pipeline_tag: text2text-generation
library_name: transformers
license: other
---
# Model Details
- **Model name:** Flan-UL2-Alpaca-LoRA
- **Model type:** - Text2Text Generation
- **Parent Model:** [google/flan-ul2](https://huggingface.co/google/flan-ul2)
- **Training d... | [
-0.01962761953473091,
-0.027519680559635162,
0.005254799500107765,
0.08104025572538376,
0.03820279613137245,
0.012864651158452034,
-0.01678127609193325,
0.005899255163967609,
-0.0034820649307221174,
0.05945740267634392,
0.002923405496403575,
-0.01878270134329796,
-0.00267860502935946,
0.01... |
AnonymousSub/bert_hier_diff_equal_wts_epochs_1_shard_10 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"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": nul... | 1 | null | ---
language: ary
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: XLSR Wav2Vec2 Moroccan Arabic dialect by Boumehdi
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
metrics:
- na... | [
-0.01667574793100357,
-0.023300250992178917,
-0.016471995040774345,
0.04711185768246651,
0.04528118297457695,
0.029159244149923325,
-0.0007181972614489496,
-0.010756115429103374,
-0.03387662395834923,
0.07762980461120605,
0.025388941168785095,
-0.02877531386911869,
-0.026319287717342377,
0... |
AnonymousSub/bert_mean_diff_epochs_1_shard_1 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"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": nul... | 6 | null | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
---
# {MODEL_NAME}
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semanti... | [
-0.022738344967365265,
-0.023844456300139427,
-0.01900692656636238,
0.06017673760652542,
0.030038069933652878,
0.03279808908700943,
-0.018910249695181847,
0.007863746955990791,
-0.06443177163600922,
0.08101920783519745,
0.027643242850899696,
0.012788072228431702,
0.009424532763659954,
0.03... |
AnonymousSub/cline-emanuals-s10-SR | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: creativeml-openrail-m
---
https://civitai.com/models/4669/corneos-7th-heaven-mix | [
-0.06889702379703522,
-0.011288837529718876,
-0.005202082917094231,
-0.009580390527844429,
0.045082248747348785,
0.0005108198383823037,
-0.01653449796140194,
-0.015242848545312881,
-0.02207217365503311,
0.045395564287900925,
0.06033327057957649,
0.03268999233841896,
0.03148037567734718,
0.... |
AnonymousSub/cline_emanuals | [
"pytorch",
"roberta",
"transformers"
] | null | {
"architectures": [
"LecbertForPreTraining"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_n... | 3 | null |
---
tags:
- unity-ml-agents
- ml-agents
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-SoccerTwos
library_name: ml-agents
---
# **poca** Agent playing **SoccerTwos**
This is a trained model of a **poca** agent playing **SoccerTwos** using the [Unit... | [
-0.020878156647086143,
-0.005833523813635111,
0.00974278524518013,
0.04032643884420395,
0.03170288726687431,
0.01546261552721262,
-0.030263328924775124,
-0.016492810100317,
-0.01673789508640766,
0.061185676604509354,
0.004469405394047499,
0.0022655227221548557,
0.013233167119324207,
0.0228... |
AnonymousSub/cline_squad2.0 | [
"pytorch",
"roberta",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"RobertaForQuestionAnswering"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 8 | null | ---
license: creativeml-openrail-m
tags:
- text-to-image
- stable-diffusion
---
### zephyrs-diffusion-v1 Dreambooth model trained by decept1on 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 A1... | [
-0.011899283155798912,
-0.021464040502905846,
-0.027823403477668762,
0.038674864917993546,
0.03431147336959839,
0.009517877362668514,
0.006947012152522802,
0.006039462983608246,
-0.002444442128762603,
0.031913213431835175,
0.03736959770321846,
0.013392110355198383,
-0.008725675754249096,
0... |
AnonymousSub/cline_wikiqa | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"RobertaForSequenceClassification"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"... | 27 | null | ---
tags:
- spacy
- text-classification
language:
- es
model-index:
- name: es_pipeline
results: []
widget:
- text: "¿Qué es lo que te pasa pues a vos, parce?"
metrics:
- accuracy
pipeline_tag: text-classification
---
| Feature | Description |
| --- | --- |
| **Name** | `es_pipeline` |
| **Version** | `0.0.0` |
| **s... | [
-0.002216570544987917,
-0.02015681192278862,
-0.007973920553922653,
0.03472097963094711,
0.061706434935331345,
0.021680617704987526,
-0.010135280899703503,
0.006798288784921169,
-0.03221448138356209,
0.0526936911046505,
0.01740422658622265,
-0.0058458964340388775,
0.006189904175698757,
0.0... |
AnonymousSub/consert-s10-SR | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 28 | null | ---
license: other
---
LLaMA converted to Transformers. This is under a special license, please see the LICENSE file for details.
# LLaMA Model Card
https://github.com/facebookresearch/llama/blob/main/MODEL_CARD.md
# Torrent 7-65B
Note: the torrent has outdated tokenizer_config.json and special_tokens_map.json. Repla... | [
-0.05367092788219452,
-0.008774930611252785,
-0.026263559237122536,
0.010492012836039066,
0.026322590187191963,
0.034915126860141754,
0.005868053995072842,
-0.0140422023832798,
-0.011390537954866886,
0.04770837351679802,
0.05378708243370056,
-0.0076285311952233315,
0.023927798494696617,
0.... |
AnonymousSub/declutr-emanuals-s10-SR | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"RobertaForSequenceClassification"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"... | 28 | 2023-04-06T00:25:31Z | ---
metrics:
- accuracy
- bertscore
- bleu
- bleurt
- brier_score
- cer
- character
- charcut_mt
- chrf
- code_eval
library_name: adapter-transformers
pipeline_tag: text2text-generation
tags:
- finance
- code
- legal
- biology
- chemistry
- music
datasets:
- Intel/CoreSearch
- facebook/babi_qa
- google/xtreme_s
---
# M... | [
-0.02253330498933792,
-0.00024053289962466806,
-0.001183124608360231,
0.02083841897547245,
0.01735980436205864,
0.03617674112319946,
-0.01840990036725998,
-0.016751902177929878,
-0.029693933203816414,
0.05076102167367935,
0.03894855082035065,
-0.011210220865905285,
0.0029325527139008045,
0... |
AnonymousSub/declutr-model-emanuals | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngra... | 4 | 2023-04-06T00:32:19Z | ---
license: other
---
LLaMA converted to Transformers. This is under a special license, please see the LICENSE file for details.
# LLaMA Model Card
https://github.com/facebookresearch/llama/blob/main/MODEL_CARD.md
# Torrent 7-65B
Note: the torrent has outdated tokenizer_config.json and special_tokens_map.json. Repla... | [
-0.05367092788219452,
-0.008774930611252785,
-0.026263559237122536,
0.010492012836039066,
0.026322590187191963,
0.034915126860141754,
0.005868053995072842,
-0.0140422023832798,
-0.011390537954866886,
0.04770837351679802,
0.05378708243370056,
-0.0076285311952233315,
0.023927798494696617,
0.... |
AnonymousSub/declutr-model_squad2.0 | [
"pytorch",
"roberta",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"RobertaForQuestionAnswering"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 2 | null |
---
tags:
- unity-ml-agents
- ml-agents
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-SoccerTwos
library_name: ml-agents
---
# **poca** Agent playing **SoccerTwos**
This is a trained model of a **poca** agent playing **SoccerTwos** using the [Unit... | [
-0.02160707302391529,
-0.00439424766227603,
0.010945895686745644,
0.03854222968220711,
0.030860578641295433,
0.015843089669942856,
-0.028232358396053314,
-0.015309709124267101,
-0.01581842452287674,
0.061921074986457825,
0.006633642129600048,
0.000015823861758690327,
0.01135973446071148,
0... |
AnonymousSub/declutr-roberta-papers | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngra... | 4 | 2023-04-06T00:47:40Z | ---
library_name: ml-agents
tags:
- Huggy
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-Huggy
---
# **ppo** Agent playing **Huggy**
This is a trained model of a **ppo** agent playing **Huggy** using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
## Usage (... | [
-0.039184872061014175,
-0.0011989031918346882,
-0.008566508069634438,
0.04702965170145035,
0.025237832218408585,
0.01838277466595173,
-0.025727933272719383,
-0.03320107236504555,
-0.0036360309459269047,
0.049740470945835114,
0.02062300406396389,
-0.01303076557815075,
0.018013479188084602,
... |
AnonymousSub/declutr-s10-AR | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"RobertaForSequenceClassification"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"... | 26 | 2023-04-06T00:53:12Z | ---
license: other
---
LLaMA converted to Transformers. This is under a special license, please see the LICENSE file for details.
# LLaMA Model Card
https://github.com/facebookresearch/llama/blob/main/MODEL_CARD.md
# Torrent 7-65B
Note: the torrent has outdated tokenizer_config.json and special_tokens_map.json. Repla... | [
-0.05367092788219452,
-0.008774930611252785,
-0.026263559237122536,
0.010492012836039066,
0.026322590187191963,
0.034915126860141754,
0.005868053995072842,
-0.0140422023832798,
-0.011390537954866886,
0.04770837351679802,
0.05378708243370056,
-0.0076285311952233315,
0.023927798494696617,
0.... |
AnonymousSub/rule_based_bert_hier_diff_equal_wts_epochs_1_shard_1 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"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": nul... | 8 | null | ---
license: apache-2.0
inference: false
---
**NOTE: New version available**
Please check out a newer version of the weights at https://huggingface.co/lmsys/vicuna-7b-delta-v1.1
If you still want to use this old version, please see the compatibility and difference between different versions at https://github.com/l... | [
-0.029323210939764977,
-0.018501335754990578,
-0.004903009161353111,
0.04016534239053726,
0.03804665431380272,
0.0182704646140337,
0.009987974539399147,
0.008579685352742672,
0.00628846138715744,
0.037148259580135345,
0.04576200991868973,
0.0019208753947168589,
0.027136461809277534,
0.0534... |
AnonymousSub/rule_based_bert_quadruplet_epochs_1_shard_1_squad2.0 | [
"pytorch",
"bert",
"question-answering",
"transformers",
"autotrain_compatible"
] | 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... | 3 | null | ---
tags:
- Pixelcopter-PLE-v0
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: Reinforce-cartpole
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Pixelcopter-PLE-v0
type: Pixelcopter-PLE-v0
me... | [
-0.04195110499858856,
0.020433934405446053,
0.011908413842320442,
0.012279264628887177,
0.05134807899594307,
-0.021375974640250206,
-0.01640939526259899,
-0.024029793217778206,
-0.024312328547239304,
0.07513992488384247,
0.032012660056352615,
-0.012391479685902596,
0.012818126007914543,
-0... |
AnonymousSub/rule_based_bert_triplet_epochs_1_shard_1_wikiqa | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 31 | null | ---
license: openrail
datasets:
- bigcode/the-stack
language:
- code
programming_language:
- Java
- JavaScript
- Python
pipeline_tag: text-generation
inference: false
model-index:
- name: SantaCoder
results:
- task:
type: text-generation
dataset:
type: nuprl/MultiPL-E
name: MultiPL HumanEval... | [
-0.010572741739451885,
-0.04178620129823685,
-0.026271924376487732,
0.01739449054002762,
0.06886070221662521,
0.031315434724092484,
-0.0402747243642807,
-0.008133528754115105,
-0.0517108179628849,
0.06576010584831238,
0.020448695868253708,
0.0024617251474410295,
0.007255761418491602,
0.044... |
AnonymousSub/rule_based_hier_quadruplet_epochs_1_shard_1 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"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": nul... | 8 | null | ---
library_name: sample-factory
tags:
- deep-reinforcement-learning
- reinforcement-learning
- sample-factory
model-index:
- name: APPO
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: doom_health_gathering_supreme
type: doom_health_gathering_sup... | [
-0.04552450403571129,
-0.0017331050476059318,
0.011267836205661297,
0.03839583694934845,
0.024902326986193657,
-0.009661687538027763,
-0.009554492309689522,
-0.023574940860271454,
-0.03720926493406296,
0.05549835041165352,
0.034488748759031296,
0.0027857960667461157,
0.018719160929322243,
... |
AnonymousSub/rule_based_hier_quadruplet_epochs_1_shard_10 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"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": nul... | 4 | null | ---
tags:
- generated_from_trainer
model-index:
- name: ParroT-7b
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 comment. -->
# ParroT-7b
This model is a fine-tuned version... | [
-0.030019380152225494,
-0.010401823557913303,
-0.01859034225344658,
0.06980960071086884,
0.03411095216870308,
0.02081635780632496,
0.010297449305653572,
-0.0014390830183401704,
-0.04197284206748009,
0.05409320071339607,
0.03500567376613617,
-0.033937208354473114,
0.008222632110118866,
0.03... |
AnonymousSub/rule_based_hier_quadruplet_epochs_1_shard_1_squad2.0 | [
"pytorch",
"bert",
"question-answering",
"transformers",
"autotrain_compatible"
] | 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... | 3 | null | ---
license: creativeml-openrail-m
library_name: diffusers
pipeline_tag: text-to-image
tags:
- stable-diffusion
- aiartchan
---
# MIX-Pro-V4
[원본글](https://arca.live/b/aiart/73277342)
[huggingface](https://huggingface.co/GIMG/AIChan_Model/tree/main/Blend/MIX-Pro/V4)
[civitai](https://civitai.com/models/7241)
# Down... | [
-0.015595230273902416,
-0.02011296898126602,
-0.005715630017220974,
0.02779265306890011,
0.01640680991113186,
0.020453637465834618,
0.00004255904059391469,
-0.015570581890642643,
-0.012511298060417175,
0.059100229293107986,
0.015275170095264912,
0.003449356649070978,
0.012069462798535824,
... |
AnonymousSub/rule_based_only_classfn_epochs_1_shard_1_squad2.0 | [
"pytorch",
"bert",
"question-answering",
"transformers",
"autotrain_compatible"
] | 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... | 2 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- afrispeech-200
metrics:
- wer
model-index:
- name: whisper-medium-23
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: afrispeech-200
type: afrispeech-200
config: ... | [
-0.02258976548910141,
-0.00012016929395031184,
-0.018024932593107224,
0.03971562534570694,
0.04546985775232315,
0.02827855385839939,
-0.0022038593888282776,
-0.004677676595747471,
-0.02577904798090458,
0.07333510369062424,
0.029884159564971924,
-0.025426344946026802,
0.003350825048983097,
... |
AnonymousSub/rule_based_only_classfn_twostage_epochs_1_shard_1 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"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": nul... | 10 | 2023-04-06T02:25:45Z | ---
tags:
- alpaca
- instruction
- pythia
---
All IPythia models were trained on an internal GerbilLab high quality instruction dataset of ~75k instructions for 3 epochs. Prompt format:
```
Instruction: [instruction goes here]
Input: [input goes here]
Output: [output will be generated here]
or
Instruction: [instruc... | [
-0.022779202088713646,
0.0072126672603189945,
-0.012747028842568398,
0.03585048392415047,
0.03592068701982498,
0.01881455071270466,
-0.0027108686044812202,
-0.0031017372384667397,
0.0010694715892896056,
0.06961334496736526,
0.04565202444791794,
-0.027520857751369476,
-0.015582915395498276,
... |
AnonymousSub/rule_based_only_classfn_twostage_epochs_1_shard_1_wikiqa | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 27 | 2023-04-06T02:30:09Z | ---
language:
- en
tags:
- geov
---
Prompt Format:
```
[instruction]
[optional input]
[response will start after two newlines]
```
```python
!pip install -q bitsandbytes datasets accelerate loralib
!pip install -q git+https://github.com/huggingface/transformers.git@main git+https://github.com/huggingface/peft.git
... | [
-0.02262415550649166,
-0.021178290247917175,
-0.0011366511462256312,
0.04165517911314964,
0.026887593790888786,
0.00878070667386055,
-0.019594455137848854,
-0.011182052083313465,
-0.05242186784744263,
0.06090301647782326,
0.024524029344320297,
0.021792005747556686,
0.007945933379232883,
0.... |
AnonymousSub/rule_based_roberta_bert_quadruplet_epochs_1_shard_10 | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"model_type": "roberta",
"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 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
config: split... | [
-0.010357904247939587,
0.009563722647726536,
-0.02909979037940502,
0.03615070506930351,
0.06113067641854286,
0.03290326148271561,
-0.022963838651776314,
-0.035826899111270905,
-0.03416850417852402,
0.05718227103352547,
0.018343951553106308,
-0.046732332557439804,
0.03455476090312004,
0.044... |
AnonymousSub/rule_based_twostagequadruplet_hier_epochs_1_shard_1 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"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": nul... | 1 | 2023-04-06T04:19:42Z | ---
license: openrail
---
JUST MIRRORING FOR COLAB FROM : https://civitai.com/models/2661/uber-realistic-porn-merge-urpm | [
-0.019690057262778282,
0.004659690894186497,
-0.012137122452259064,
0.03958887979388237,
0.020810075104236603,
0.030505914241075516,
0.012832723557949066,
-0.0022851035464555025,
-0.026957504451274872,
0.035833943635225296,
0.07665500789880753,
0.02814735658466816,
0.00015969574451446533,
... |
AnonymousSub/unsup-consert-papers | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"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": nul... | 2 | null | ---
license: apache-2.0
datasets:
- fka/awesome-chatgpt-prompts
language:
- en
- bn
metrics:
- accuracy
- character
- bleu
library_name: adapter-transformers
pipeline_tag: text-classification
tags:
- chemistry
- art
- code
--- | [
-0.01455138809978962,
-0.023263899609446526,
0.02092304266989231,
0.012511782348155975,
0.0412369966506958,
0.006297817453742027,
-0.006110717076808214,
0.012548020109534264,
-0.01044529490172863,
0.03960227593779564,
0.015032337978482246,
0.015704795718193054,
0.009399456903338432,
0.0393... |
Anonymreign/savagebeta | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | 2023-04-06T05:11:48Z | ---
license: apache-2.0
pipeline_tag: text-classification
---
Gerekli kütüphaneler
-----
keras 2.12.0 \
matplotlib 3.7.1 \
numpy 1.22.4 \
pandas 1.4.4 \
seaborn 0.12.2 \
session_info 1.0.0 \
sklearn 1.2.2 \
tensorflow 2.12.0 \
tor... | [
-0.015410693362355232,
-0.016706079244613647,
0.0023117612581700087,
0.025820191949605942,
0.05856781825423241,
0.009784053079783916,
-0.016902882605791092,
0.006338710431009531,
-0.035826556384563446,
0.06537680327892303,
0.0171367060393095,
-0.0033361008390784264,
0.013841196894645691,
0... |
Anthos23/FS-distilroberta-fine-tuned | [
"pytorch",
"roberta",
"text-classification",
"transformers",
"has_space"
] | text-classification | {
"architectures": [
"RobertaForSequenceClassification"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"... | 33 | null | ---
license: mit
---
### ahx-beta-42e55a7 on Stable Diffusion
This is the `<ahx-beta-42e55a7>` concept taught to Stable Diffusion via Textual Inversion. You can load this concept into the [Stable Conceptualizer](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_conceptualizer_inf... | [
-0.026851540431380272,
-0.023856915533542633,
-0.032598186284303665,
0.04323875159025192,
0.009483378380537033,
0.01919637620449066,
0.0038239399436861277,
-0.010441763326525688,
-0.031549423933029175,
0.03685437887907028,
-0.005193490069359541,
-0.008542941883206367,
0.03262178972363472,
... |
ArBert/bert-base-uncased-finetuned-ner-kmeans-twitter | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | 2023-04-06T06:23:19Z | ---
license: other
tags:
- generated_from_keras_callback
model-index:
- name: nizar-sayad/opt-350m-finetuned-openbookcorpus
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. ... | [
-0.03269272297620773,
-0.025470301508903503,
0.000051569732022471726,
0.01069209910929203,
0.025072528049349785,
0.02911864034831524,
-0.03005886822938919,
-0.0020914210472255945,
-0.01791193149983883,
0.059308379888534546,
0.05126791447401047,
-0.000498170149512589,
0.018211858347058296,
... |
ArBert/bert-base-uncased-finetuned-ner-kmeans | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"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... | 6 | 2023-04-06T06:23:23Z | ---
license: mit
---
### miumiu on Stable Diffusion
This is the `<miumiu>` concept taught to Stable Diffusion via Textual Inversion. You can load this concept into the [Stable Conceptualizer](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_conceptualizer_inference.ipynb) notebo... | [
-0.03325086832046509,
-0.021303273737430573,
-0.02709612064063549,
0.040201883763074875,
0.004189344123005867,
0.01601020246744156,
0.00556813133880496,
-0.010770652443170547,
-0.03875452280044556,
0.04541116580367088,
0.011781979352235794,
-0.00641839113086462,
0.041346415877342224,
0.032... |
Aybars/ModelOnWhole | [
"pytorch",
"bert",
"question-answering",
"transformers",
"autotrain_compatible"
] | 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... | 4 | null | ---
license: creativeml-openrail-m
---
https://civitai.com/models/27862/android-18-18-dragon-ball-z | [
-0.02080630324780941,
-0.001681576599366963,
-0.0014302157796919346,
0.009476921521127224,
0.05015195533633232,
0.01715276949107647,
-0.007695562206208706,
0.0013255964731797576,
-0.016567982733249664,
0.012524702586233616,
0.0595744289457798,
-0.0028693058993667364,
0.062158141285181046,
... |
Aybars/XLM_Turkish | [
"pytorch",
"xlm-roberta",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"XLMRobertaForQuestionAnswering"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 4 | null | ---
license: creativeml-openrail-m
---
https://civitai.com/models/20955/iowa-kancolle-released | [
-0.0417204312980175,
-0.016683470457792282,
-0.00824423786252737,
0.026890486478805542,
0.03472265601158142,
-0.00230358075350523,
-0.0070837573148310184,
-0.003924057353287935,
-0.032188985496759415,
0.045906584709882736,
0.061851873993873596,
0.0018483176827430725,
0.043102897703647614,
... |
Ayham/roberta_distilgpt2_summarization_cnn_dailymail | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 4 | null | ---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: xlm-roberta-base-finetuned-panx-all
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 comment.... | [
-0.03995572030544281,
-0.009709693491458893,
0.003690446726977825,
0.032717205584049225,
0.023060739040374756,
0.0224753525108099,
-0.017470279708504677,
-0.00419048685580492,
-0.027377190068364143,
0.047394461929798126,
0.025345508009195328,
-0.049668602645397186,
0.022193586453795433,
0.... |
Ayham/roberta_gpt2_new_max64_summarization_cnndm | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 4 | null | ---
license: apache-2.0
tags:
- classification
- generated_from_trainer
model-index:
- name: languagedetectionclassification
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... | [
-0.0319836400449276,
-0.010036329738795757,
-0.028265807777643204,
0.061019416898489,
0.03996598720550537,
0.02561044879257679,
-0.007443860173225403,
-0.024432990700006485,
-0.0494985468685627,
0.07025647908449173,
0.005357533693313599,
-0.028753861784934998,
0.017577415332198143,
0.03814... |
Ayham/roberta_roberta_summarization_cnn_dailymail | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 3 | 2023-04-06T09:50:23Z | ---
language: ru
tags:
- audio
- automatic-speech-recognition
- speech
- PyTorch
- Transformers
license: apache-2.0
widget:
- text: уласны в москве интерне только в большом году что лепровели
---
# ruT5-ASR
Model was trained by [bond005](https://research.nsu.ru/en/persons/ibondarenko) to correct errors in t... | [
-0.017899489030241966,
-0.023332946002483368,
0.0076218582689762115,
0.05389757454395294,
0.04472503811120987,
0.016538970172405243,
-0.029384076595306396,
-0.011705681681632996,
-0.06757906824350357,
0.044678591191768646,
0.0368058979511261,
-0.011950348503887653,
-0.02634657546877861,
0.... |
Azuris/DialoGPT-medium-senorita | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 14 | null | ---
license: other
---
LLaMA-7B converted to ONNX using optimum library. This is under a special license, please see the LICENSE file for details.
https://github.com/huggingface/optimum/pull/922
Command: `optimum-cli export onnx --model decapoda-research/llama-7b-hf --task causal-lm-with-past --for-ort llama-onnx`
... | [
-0.02850302867591381,
-0.007532945368438959,
-0.00415772944688797,
0.03860823065042496,
0.03692803531885147,
0.03490165248513222,
-0.005763189401477575,
-0.020390262827277184,
-0.007286400999873877,
0.046979691833257675,
0.05565445125102997,
-0.017872288823127747,
0.006064578425139189,
0.0... |
Bagus/wav2vec2-xlsr-japanese-speech-emotion-recognition | [
"pytorch",
"wav2vec2",
"audio-classification",
"ja",
"dataset:jtes",
"transformers",
"audio",
"speech",
"speech-emotion-recognition",
"has_space"
] | audio-classification | {
"architectures": [
"HubertForSequenceClassification"
],
"model_type": "wav2vec2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"... | 26 | null | ---
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 ... | [
-0.026886053383350372,
-0.02789396420121193,
-0.01619999296963215,
0.014560681767761707,
0.020633114501833916,
0.0011162296868860722,
-0.019808335229754448,
-0.014735542237758636,
-0.03835379704833031,
0.04765520617365837,
0.01777876541018486,
-0.008775229565799236,
0.021097518503665924,
0... |
Bala/model_name | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: SETH_5e-05_0404_ES6_strict_tok
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it... | [
-0.01053847000002861,
-0.008811022154986858,
-0.0018624408403411508,
0.026601186022162437,
0.017308570444583893,
0.020067643374204636,
-0.01631835475564003,
-0.01703975349664688,
-0.02563406713306904,
0.05394325405359268,
0.02775433100759983,
-0.04697380214929581,
0.02628432586789131,
0.03... |
Battlehooks/distilbert-base-uncased-finetuned-squad | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | 2023-04-06T12:30:50Z | ---
license: creativeml-openrail-m
tags:
- text-to-image
- stable-diffusion
---
| [
-0.01000235415995121,
-0.015769654884934425,
-0.027736864984035492,
0.003522281302139163,
0.051111605018377304,
-0.009966407902538776,
0.012961309403181076,
0.019618680700659752,
-0.016439884901046753,
0.038300976157188416,
0.03102455846965313,
0.008117465302348137,
0.017173605039715767,
0... |
BatuhanYilmaz/bert-finetuned-mrpc | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: gelectra-base-injection-pt_v1
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 comment.... | [
-0.007288591004908085,
-0.004519654903560877,
-0.009746740572154522,
0.032661598175764084,
0.037124041467905045,
0.03040674515068531,
-0.0031971323769539595,
-0.005753807723522186,
-0.023161718621850014,
0.047744348645210266,
0.034935250878334045,
-0.012615925632417202,
0.002361988415941596,... |
BatuhanYilmaz/code-search-net-tokenizer1 | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
tags:
- generated_from_trainer
model-index:
- name: science
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 comment. -->
# science
This model is a fine-tuned version of ... | [
-0.030669819563627243,
-0.017262034118175507,
-0.0002391544112470001,
0.04557018354535103,
0.03939558193087578,
0.01106695644557476,
-0.0016230059554800391,
-0.01080882828682661,
-0.04428858309984207,
0.0448126494884491,
0.022889772430062294,
-0.02329675666987896,
0.005703343544155359,
0.0... |
BatuhanYilmaz/distilbert-base-uncased-finetuned-squad-d5716d28 | [
"pytorch",
"distilbert",
"fill-mask",
"en",
"dataset:squad",
"arxiv:1910.01108",
"transformers",
"question-answering",
"license:apache-2.0",
"autotrain_compatible"
] | question-answering | {
"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... | 18 | null | ---
library_name: stable-baselines3
tags:
- SpaceInvadersNoFrameskip-v4
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: DQN
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: SpaceInvadersNoFrameskip-v4
... | [
-0.04089746251702309,
-0.014870514161884785,
-0.017030928283929825,
0.0370158888399601,
0.04890454187989235,
-0.0044944994151592255,
-0.014362677000463009,
-0.024599216878414154,
-0.03041977994143963,
0.05354344844818115,
0.022914592176675797,
-0.03311620652675629,
0.019502324983477592,
0.... |
BatuhanYilmaz/dummy-model | [
"tf",
"camembert",
"fill-mask",
"transformers",
"generated_from_keras_callback",
"license:mit",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"CamembertForMaskedLM"
],
"model_type": "camembert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_... | 6 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: mT5_kimeru-english-v2.1
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 comment. --... | [
-0.03152364864945412,
-0.002620948012918234,
-0.001227637636475265,
0.035938527435064316,
0.03292539715766907,
0.00574513478204608,
-0.009729504585266113,
-0.0119375791400671,
-0.047386061400175095,
0.0561336874961853,
0.007882111705839634,
-0.0478980652987957,
0.010362420231103897,
0.0247... |
BatuhanYilmaz/mt5-small-finetuned-amazonbooks-en-es | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: tmvar_2e-05_0404_ES6_strict_tok
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete i... | [
-0.011682729236781597,
-0.00993802398443222,
-0.0012442131992429495,
0.03096965327858925,
0.02080109529197216,
0.014963259920477867,
-0.00807936117053032,
-0.018487203866243362,
-0.020009705796837807,
0.050411663949489594,
0.02401353418827057,
-0.05107233673334122,
0.02985478937625885,
0.0... |
Baybars/wav2vec2-xls-r-300m-cv8-turkish | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"tr",
"dataset:common_voice",
"transformers",
"common_voice",
"generated_from_trainer",
"hf-asr-leaderboard",
"robust-speech-event",
"license:apache-2.0"
] | automatic-speech-recognition | {
"architectures": [
"Wav2Vec2ForCTC"
],
"model_type": "wav2vec2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_s... | 5 | 2023-04-06T12:51:27Z | ---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: tmvar_5e-05_0404_ES6_strict_tok
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete i... | [
-0.010823031887412071,
-0.010164722800254822,
-0.0018852853681892157,
0.031016679480671883,
0.02065034955739975,
0.015744555741548538,
-0.008569865487515926,
-0.019414933398365974,
-0.01984851248562336,
0.05006160959601402,
0.025653354823589325,
-0.05120738595724106,
0.02994699403643608,
0... |
BeIR/query-gen-msmarco-t5-base-v1 | [
"pytorch",
"jax",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"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... | 1,816 | null | ---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: tmvar_0.0001_0404_ES6_strict_tok
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete ... | [
-0.010526933707296848,
-0.009974848479032516,
-0.0009905108017846942,
0.031209567561745644,
0.018353503197431564,
0.015346485190093517,
-0.009590056724846363,
-0.017648762091994286,
-0.020809423178434372,
0.051016610115766525,
0.022366734221577644,
-0.05123661085963249,
0.029879776760935783,... |
BeIR/query-gen-msmarco-t5-large-v1 | [
"pytorch",
"jax",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"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... | 1,225 | null | ---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: Yepes_2e-05_0404_ES6_strict_tok
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete i... | [
-0.010761287063360214,
-0.011288860812783241,
0.007286495063453913,
0.022343693301081657,
0.017266126349568367,
0.015667524188756943,
-0.009728854522109032,
-0.019957760348916054,
-0.021313942968845367,
0.05689418315887451,
0.016596022993326187,
-0.050053827464580536,
0.037759751081466675,
... |
BearThreat/distilbert-base-uncased-finetuned-cola | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:glue",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | 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,
... | 30 | null | ---
license: other
library_name: transformers
pipeline_tag: text-generation
datasets:
- RyokoAI/ShareGPT52K
- Hello-SimpleAI/HC3
tags:
- koala
- ShareGPT
- llama
- gptq
inference: false
---
# Koala: A Dialogue Model for Academic Research
This repo contains the weights of the Koala model produced at Berkeley. It is the... | [
-0.05369578301906586,
-0.016399318352341652,
0.0013745457399636507,
0.028877032920718193,
0.04414868727326393,
0.018341803923249245,
0.006718278396874666,
0.0013611618196591735,
-0.03695959597826004,
0.058306075632572174,
0.0338052362203598,
-0.027207793667912483,
0.036889102309942245,
0.0... |
Bee-Garbs/DialoGPT-cartman-small | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: Yepes_5e-05_0404_ES6_strict_tok
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete i... | [
-0.01027572713792324,
-0.010453545488417149,
0.006424533668905497,
0.02315589413046837,
0.01750008761882782,
0.015834691002964973,
-0.010188178159296513,
-0.022315172478556633,
-0.021238485351204872,
0.05608513578772545,
0.01843218319118023,
-0.051004014909267426,
0.0364607535302639,
0.040... |
Belin/T5-Terms-and-Conditions | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: Variome_2e-05_0404_ES6_strict_tok
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete... | [
-0.01369406096637249,
-0.01677507720887661,
0.011447697877883911,
0.024281729012727737,
0.023533964529633522,
0.006246326956897974,
0.0022109621204435825,
-0.01909947395324707,
-0.020804326981306076,
0.054802194237709045,
0.025036679580807686,
-0.05004611238837242,
0.03350992873311043,
0.0... |
BenDavis71/GPT-2-Finetuning-AIRaid | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 10 | null | ---
library_name: ml-agents
tags:
- SnowballTarget
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-SnowballTarget
---
# **ppo** Agent playing **SnowballTarget**
This is a trained model of a **ppo** agent playing **SnowballTarget** using the [Unity ML-Agents Library](https://github.com/Unity-Tech... | [
-0.030024047940969467,
-0.004530023317784071,
-0.01774509809911251,
0.05210762843489647,
0.035922978073358536,
0.025817638263106346,
-0.0012091653188690543,
-0.03408081457018852,
-0.02501746080815792,
0.046132367104291916,
0.026533223688602448,
-0.008730332367122173,
0.018055198714137077,
... |
BenGeorge/MyModel | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
tags:
- Taxi-v3
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-Taxi-v3
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Taxi-v3
type: Taxi-v3
metrics:
- type: mean_reward
value: 7.54 +/- 2.70... | [
-0.02123495191335678,
-0.016622373834252357,
-0.005154085345566273,
0.024807466194033623,
0.04471152275800705,
-0.002661003964021802,
-0.017938144505023956,
0.007229960057884455,
-0.03821609169244766,
0.04520915076136589,
0.020131001248955727,
-0.007575260475277901,
0.008273493498563766,
0... |
BenQLange/HF_bot | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
library_name: stable-baselines3
tags:
- LunarLander-v2
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: PPO
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: LunarLander-v2
type: LunarLander-v2
... | [
-0.03738851100206375,
-0.002627527341246605,
-0.0052213543094694614,
0.025460995733737946,
0.045377083122730255,
-0.021592335775494576,
-0.005228383932262659,
-0.027858084067702293,
-0.03347092866897583,
0.06677170097827911,
0.03239088132977486,
-0.023599840700626373,
0.022466285154223442,
... |
BenWitter/DialoGPT-small-Tyrion | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 11 | null | ---
license: mit
mask_token: '[MASK]'
tags:
- generated_from_keras_callback
model-index:
- name: tf-tpu/roberta-base-epochs-500-no-wd
results: []
widget:
- text: Goal of my life is to [MASK].
datasets:
- wikitext
---
<!-- This model card has been generated automatically according to the information Keras had access ... | [
-0.031026573851704597,
-0.026036109775304794,
0.004547891207039356,
0.02479676716029644,
0.030686138197779655,
0.02030232734978199,
-0.011438536457717419,
-0.013808260671794415,
-0.02718270942568779,
0.06577872484922409,
0.011090435087680817,
-0.00905687641352415,
0.021516742184758186,
0.0... |
Beri/legal-qa | [
"pytorch",
"roberta",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"RobertaForQuestionAnswering"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 10 | null | ---
license: creativeml-openrail-m
tags:
- text-to-image
- stable-diffusion
---
### /-copper_SD_V2-1 Dreambooth model trained by Tinsae 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 Col... | [
-0.04916159808635712,
-0.007906311191618443,
-0.02570277824997902,
0.04105865955352783,
0.028587499633431435,
0.00786659773439169,
-0.00408356636762619,
0.00038583195419050753,
-0.023975353688001633,
0.03615642711520195,
0.028601981699466705,
0.00974991824477911,
-0.018115853890776634,
0.0... |
BertChristiaens/EmojiPredictor | [
"pytorch",
"distilbert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"DistilBertForTokenClassification"
],
"model_type": "distilbert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 6 | null | ---
library_name: ml-agents
tags:
- Pyramids
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-Pyramids
---
# **ppo** Agent playing **Pyramids**
This is a trained model of a **ppo** agent playing **Pyramids** using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
... | [
-0.05253725126385689,
-0.0017982285935431719,
-0.0034971495624631643,
0.051469121128320694,
0.023580268025398254,
0.028692007064819336,
-0.00985465757548809,
-0.020456522703170776,
0.0007212611963041127,
0.04876725748181343,
0.027531197294592857,
-0.014845792204141617,
0.006849183700978756,
... |
Betaniaolivo/Foto | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: bigscience-bloom-rail-1.0
datasets:
- tatsu-lab/alpaca
language:
- en
pipeline_tag: text-generation
tags:
- crayon
- language-technologies
---
# Bloom 560M Finetuned on Instructions
## Credit
Code 99.99% copied from
*https://github.com/bofenghuang/vigogne*
*https://colab.research.google.com/drive/1... | [
-0.03629269450902939,
-0.009248566813766956,
0.00352120422758162,
0.044455934315919876,
0.02731592394411564,
0.00044010821147821844,
-0.007291422225534916,
-0.01955665647983551,
-0.022000029683113098,
0.06345291435718536,
0.0516979843378067,
-0.01195728313177824,
0.003697727806866169,
0.03... |
Bharathdamu/wav2vec2-large-xls-r-300m-hindi-colab | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"dataset:common_voice",
"transformers",
"generated_from_trainer",
"license:apache-2.0"
] | automatic-speech-recognition | {
"architectures": [
"Wav2Vec2ForCTC"
],
"model_type": "wav2vec2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_s... | 4 | null | ---
license: mit
tags:
- pytorch
- diffusers
- unconditional-image-generation
- diffusion-models-class
---
# Example Fine-Tuned Model for Unit 2 of the [Diffusion Models Class 🧨](https://github.com/huggingface/diffusion-models-class)
Describe your model here
## Usage
```python
from diffusers import DDPMPipeline
p... | [
-0.003727428149431944,
-0.018502309918403625,
0.014335737563669682,
0.02377612702548504,
0.03022676706314087,
0.011581121012568474,
0.0035356965381652117,
-0.0025324400048702955,
-0.01418240275233984,
0.051013171672821045,
0.013914111070334911,
0.004451022949069738,
0.02554607018828392,
0.... |
Bharathdamu/wav2vec2-large-xls-r-300m-hindi2-colab | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: tmvar_5e-05_0404_ES6_strict_tok1
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete ... | [
-0.01288664061576128,
-0.008646021597087383,
-0.0023686534259468317,
0.033146534115076065,
0.019347084686160088,
0.016506554558873177,
-0.008195205591619015,
-0.020932897925376892,
-0.019139353185892105,
0.04984428733587265,
0.02558322809636593,
-0.04962354898452759,
0.029300248250365257,
... |
Bhumika/roberta-base-finetuned-sst2 | [
"pytorch",
"tensorboard",
"roberta",
"text-classification",
"dataset:glue",
"transformers",
"generated_from_trainer",
"model-index"
] | text-classification | {
"architectures": [
"RobertaForSequenceClassification"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"... | 85 | null | ---
library_name: ml-agents
tags:
- Huggy
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-Huggy
---
# **ppo** Agent playing **Huggy**
This is a trained model of a **ppo** agent playing **Huggy** using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
## Usage (... | [
-0.04194602742791176,
-0.002499018097296357,
-0.0067971814423799515,
0.04755902290344238,
0.02397049590945244,
0.019745944067835808,
-0.025123151019215584,
-0.032670751214027405,
-0.0031370436772704124,
0.0481080487370491,
0.019875895231962204,
-0.013606209307909012,
0.01806728169322014,
0... |
Biasface/DDDC | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 14 | null | ---
license: apache-2.0
---
# Graphcore/t5-large-ipu
Optimum Graphcore is a new open-source library and toolkit that enables developers to access IPU-optimized models certified by Hugging Face. It is an extension of Transformers, providing a set of performance optimization tools enabling maximum efficiency to train a... | [
-0.033533982932567596,
-0.008996060118079185,
0.0022182133980095387,
0.03214482218027115,
0.02617618627846241,
0.025643588975071907,
-0.020633848384022713,
-0.0341419093310833,
-0.011770854704082012,
0.03519807755947113,
0.026481540873646736,
0.004325606860220432,
0.008533239364624023,
0.0... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.