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 |
|---|---|---|---|---|---|---|---|
CouchCat/ma_ner_v6_distil | [
"pytorch",
"distilbert",
"token-classification",
"en",
"transformers",
"ner",
"license:mit",
"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 | 2022-11-09T18:35:22Z | ---
license: mit
tags:
- generated_from_trainer
datasets:
- xtreme
metrics:
- f1
model-index:
- name: xlm-roberta-base-finetuned-panx-it
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: xtreme
type: xtreme
args: PAN-X.it
metrics:
- name:... | [
-0.024929208680987358,
-0.0019495714223012328,
0.004664524458348751,
0.01891707256436348,
0.02648601308465004,
0.022089386358857155,
-0.018357545137405396,
-0.009171422570943832,
-0.015330778434872627,
0.044319648295640945,
0.023581786081194878,
-0.04556332528591156,
0.019023023545742035,
... |
CouchCat/ma_ner_v7_distil | [
"pytorch",
"distilbert",
"token-classification",
"en",
"transformers",
"ner",
"license:mit",
"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,
... | 13 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: TSE_ELECTRA_5E
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. -->
# ... | [
-0.026608532294631004,
0.0013843100750818849,
0.012877704575657845,
0.026232579723000526,
0.03923719748854637,
0.014912395738065243,
-0.02436547912657261,
0.004314637742936611,
-0.042042627930641174,
0.04029514640569687,
0.006709042936563492,
-0.03739490360021591,
0.0050623356364667416,
0.... |
CouchCat/ma_sa_v7_distil | [
"pytorch",
"distilbert",
"text-classification",
"en",
"transformers",
"sentiment-analysis",
"license:mit"
] | 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,
... | 38 | null | ---
license: mit
tags:
- generated_from_trainer
datasets:
- xtreme
metrics:
- f1
model-index:
- name: xlm-roberta-base-finetuned-panx-en
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: xtreme
type: xtreme
args: PAN-X.en
metrics:
- name:... | [
-0.024217961356043816,
-0.0021978900767862797,
0.006967079825699329,
0.023275544866919518,
0.02919580228626728,
0.02342761494219303,
-0.022534357383847237,
-0.011923606507480145,
-0.02379443123936653,
0.046581611037254333,
0.01891259104013443,
-0.04681387543678284,
0.015028689056634903,
0.... |
CoveJH/ConBot | [] | 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: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: whisper_havest_0015
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. -->
# whisper_havest... | [
-0.039014074951410294,
-0.022120747715234756,
0.0066953422501683235,
0.037054307758808136,
0.03849580138921738,
0.004866553470492363,
-0.01256080437451601,
0.003157449420541525,
-0.02254374697804451,
0.06810836493968964,
0.02835688926279545,
-0.028678320348262787,
0.01656719110906124,
0.03... |
Coyotl/DialoGPT-test-last-arthurmorgan | [
"conversational"
] | conversational | {
"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: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: distilbert-base-uncased-finetuned-imdb
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. -->... | [
-0.01789727993309498,
0.006413957104086876,
-0.033093247562646866,
0.04749457538127899,
0.04867120832204819,
0.02587387152016163,
-0.01901732198894024,
-0.02542809769511223,
-0.03412025421857834,
0.06557419896125793,
0.04434692859649658,
-0.023763108998537064,
0.011932426132261753,
0.04756... |
Coyotl/DialoGPT-test3-arthurmorgan | [
"conversational"
] | conversational | {
"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: apache-2.0
tags:
- generated_from_trainer
datasets:
- squad
model-index:
- name: distilbert-base-uncased-finetuned-squad-ver2
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 ... | [
-0.02053050510585308,
-0.0076955994591116905,
-0.03205738216638565,
0.05102357268333435,
0.06257966160774231,
0.0224315132945776,
-0.030384032055735588,
0.004176674410700798,
-0.035294681787490845,
0.0513649582862854,
0.03671564534306526,
-0.02177395112812519,
0.012064511887729168,
0.04688... |
Craak/GJ0001 | [] | 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
model-index:
- name: BERiT_27000
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. -->
# BERiT_27000
This model is a f... | [
-0.013623025268316269,
-0.006950258743017912,
-0.016861533746123314,
0.031976114958524704,
0.01764099858701229,
0.018878575414419174,
-0.014212180860340595,
-0.01905810460448265,
-0.03778575733304024,
0.044463589787483215,
0.018706563860177994,
-0.036565229296684265,
0.021793462336063385,
... |
CracklesCreeper/Piglin-Talks-Harry-Potter | [
"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... | 10 | 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.... | [
-0.04164903238415718,
-0.010376103222370148,
0.0032476712949573994,
0.03313269466161728,
0.02323690615594387,
0.023075152188539505,
-0.01811515912413597,
-0.005247791297733784,
-0.027885673567652702,
0.04784270375967026,
0.02567397430539131,
-0.049539823085069656,
0.02141011878848076,
0.03... |
Craftified/Bob | [] | 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: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: whisper_havest_0020
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. -->
# whisper_havest... | [
-0.03837068751454353,
-0.02199096418917179,
0.006521675270050764,
0.03743186593055725,
0.038115717470645905,
0.005777874030172825,
-0.012886046431958675,
0.004740327596664429,
-0.022954685613512993,
0.06828948110342026,
0.028086675330996513,
-0.029817981645464897,
0.01728500798344612,
0.03... |
Craig/mGqFiPhu | [
"sentence-transformers",
"feature-extraction",
"sentence-similarity",
"transformers",
"license:apache-2.0"
] | feature-extraction | {
"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: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: TSE_DistilBERT_5E
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. -->
... | [
-0.008366517722606659,
0.0033341222442686558,
-0.009776641614735126,
0.03389754518866539,
0.042329564690589905,
0.016327595338225365,
-0.024386944249272346,
-0.0065194591879844666,
-0.041943877935409546,
0.04739158973097801,
0.01682863011956215,
-0.03584332391619682,
0.00339714833535254,
0... |
Crasher222/kaggle-comp-test | [
"pytorch",
"bert",
"text-classification",
"en",
"dataset:Crasher222/autonlp-data-kaggle-test",
"transformers",
"autonlp",
"co2_eq_emissions"
] | 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... | 29 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-burak-new-300-v2-6
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.... | [
-0.01801428757607937,
-0.006790808867663145,
-0.01730213314294815,
0.024137070402503014,
0.03768748417496681,
0.013540052808821201,
-0.011262343265116215,
0.0049542090855538845,
-0.030849142000079155,
0.05684291571378708,
0.029400372877717018,
-0.0302193071693182,
0.005913387518376112,
0.0... |
CrayonShinchan/bart_fine_tune_test | [] | 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 | ---
language:
- es
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- facebook/multilingual_librispeech
metrics:
- wer
model-index:
- name: Whisper Small Es - Sanchit Gandhi
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
datase... | [
-0.007880806922912598,
-0.005247714463621378,
-0.02285737358033657,
0.04665631055831909,
0.04314504191279411,
0.02887902222573757,
-0.02258613333106041,
-0.0013298735721036792,
-0.03914911299943924,
0.07417917251586914,
0.03451050817966461,
-0.014039422385394573,
0.011160911992192268,
0.02... |
CrayonShinchan/fine_tune_try_1 | [] | 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: apache-2.0
tags:
- generated_from_trainer
datasets:
- squad
model-index:
- name: distilbert-base-uncased-finetuned-squad-ver3
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 ... | [
-0.02232097089290619,
-0.007983808405697346,
-0.032976601272821426,
0.0498868003487587,
0.06273698061704636,
0.023913530632853508,
-0.02965022251009941,
0.002487459685653448,
-0.035371847450733185,
0.052055537700653076,
0.03713947907090187,
-0.02448391355574131,
0.011063355021178722,
0.044... |
CrisLeaf/generador-de-historias-de-tolkien | [
"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... | 8 | null | ---
license: mit
---
### Glitch on Stable Diffusion via Dreambooth
#### model by BakkerHenk
This your the Stable Diffusion model fine-tuned the Glitch concept taught to Stable Diffusion with Dreambooth.
It can be used by modifying the `instance_prompt`: **a photo in sks glitched style**
You can also train your own con... | [
-0.041724275797605515,
-0.0153611795976758,
-0.013659898191690445,
0.02274581789970398,
0.036214955151081085,
0.01845582202076912,
-0.00014949211617931724,
0.009552830830216408,
-0.03189786151051521,
0.04607566446065903,
0.01948372647166252,
-0.0043327887542545795,
-0.012603040784597397,
0... |
Crisblair/Wkwk | [] | 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: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: whisper_havest_0025
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. -->
# whisper_havest... | [
-0.03814595937728882,
-0.022243071347475052,
0.007339432369917631,
0.0382695198059082,
0.03853025287389755,
0.005444417707622051,
-0.012903395108878613,
0.00453593023121357,
-0.022702138870954514,
0.06872837245464325,
0.02801266685128212,
-0.028880544006824493,
0.016893837600946426,
0.0368... |
Crispy/dialopt-small-kratos | [] | 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
model-index:
- name: BERiT_14500
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. -->
# BERiT_14500
This model is a f... | [
-0.015315120108425617,
-0.003371261293068528,
-0.012899038381874561,
0.03233420103788376,
0.01708979159593582,
0.018745828419923782,
-0.019473960623145103,
-0.01751406118273735,
-0.04069748893380165,
0.04578377306461334,
0.015842799097299576,
-0.04027364030480385,
0.01845630817115307,
0.04... |
Crives/distilbert-base-uncased-finetuned-emotion | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"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,
... | 31 | null | ---
tags:
- image-classification
- timm
library_name: timm
license: apache-2.0
datasets:
- imagenet-1k
- laion-2b
---
# Model card for vit_base_patch16_clip_384.laion2b_ft_in1k
A Vision Transformer (ViT) image classification model. Pretrained on LAION-2B image-text pairs using OpenCLIP. Fine-tuned on ImageNet-1k in `t... | [
-0.025912266224622726,
-0.027720432728528976,
0.003053547814488411,
0.035580798983573914,
0.03142775967717171,
-0.0073311664164066315,
-0.0033484669402241707,
-0.008289217948913574,
-0.003862434532493353,
0.05152256041765213,
0.022946685552597046,
0.00044123511179350317,
-0.00325017143040895... |
Crumped/imdb-simpleRNN | [
"keras"
] | 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_name: timm
license: apache-2.0
datasets:
- imagenet-1k
- wit-400m
---
# Model card for vit_base_patch16_clip_384.openai_ft_in1k
A Vision Transformer (ViT) image classification model. Pretrained on WIT-400M image-text pairs by OpenAI using CLIP. Fine-tuned on ImageNet-1k ... | [
-0.028682196512818336,
-0.02662103995680809,
0.003823190461844206,
0.035433221608400345,
0.03269939497113228,
-0.0010859622852876782,
-0.002331842901185155,
-0.0020760013721883297,
0.0003806991735473275,
0.053879160434007645,
0.023635346442461014,
-0.0011674003908410668,
-0.00718025676906108... |
CrypticT1tan/DialoGPT-medium-harrypotter | [] | 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
metrics:
- accuracy
- f1
model-index:
- name: finetuning-sentiment-hausa2
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. -->
# fi... | [
-0.029149914160370827,
-0.014044840820133686,
0.003257719101384282,
0.027461308985948563,
0.019428709521889687,
0.025284217670559883,
-0.013591652736067772,
-0.006961947772651911,
-0.04642367362976074,
0.05232015624642372,
0.027047736570239067,
-0.024864239618182182,
0.01538559515029192,
0... |
Culmenus/IceBERT-finetuned-ner | [
"pytorch",
"tensorboard",
"roberta",
"token-classification",
"dataset:mim_gold_ner",
"transformers",
"generated_from_trainer",
"license:gpl-3.0",
"model-index",
"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_... | 5 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- squad
model-index:
- name: distilbert-base-uncased-finetuned-squad-ver4
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 ... | [
-0.023071778938174248,
-0.005909092258661985,
-0.032626405358314514,
0.050096094608306885,
0.06171388551592827,
0.02349022775888443,
-0.029791317880153656,
0.0026206173934042454,
-0.036690372973680496,
0.05200981721282005,
0.03552830591797829,
-0.024660157039761543,
0.014427612535655499,
0... |
Culmenus/XLMR-ENIS-finetuned-ner | [
"pytorch",
"tensorboard",
"xlm-roberta",
"token-classification",
"dataset:mim_gold_ner",
"transformers",
"generated_from_trainer",
"license:agpl-3.0",
"model-index",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"XLMRobertaForTokenClassification"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 6 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- librispeech_asr
metrics:
- wer
model-index:
- name: whisper-small-en
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: librispeech_asr
type: librispeech_asr
config... | [
-0.023723693564534187,
-0.0029061632230877876,
-0.015158791095018387,
0.04922228679060936,
0.03900279104709625,
0.015653599053621292,
-0.00365924509242177,
-0.007181875873357058,
-0.03547529876232147,
0.07842753082513809,
0.02764955163002014,
-0.024335334077477455,
0.006639895960688591,
0.... |
Culmenus/checkpoint-168500-finetuned-de-to-is_nr2 | [] | 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 | ---
language: en
tags:
- exbert
license: apache-2.0
datasets:
- bookcorpus
- wikipedia
---
# BERT base model (cased)
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1810.04805) and first released in
[this repository](https:... | [
-0.005537884775549173,
0.0068740639835596085,
-0.01787860319018364,
0.06503400951623917,
0.026847530156373978,
0.033723000437021255,
-0.01929895021021366,
-0.03633744642138481,
-0.03174727410078049,
0.04941345006227493,
0.015982916578650475,
-0.005766472313553095,
0.016170065850019455,
0.0... |
Culmenus/opus-mt-de-is-finetuned-de-to-is | [
"pytorch",
"marian",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"MarianMTModel"
],
"model_type": "marian",
"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: zh
---
# Bert-base-chinese
## Table of Contents
- [Model Details](#model-details)
- [Uses](#uses)
- [Risks, Limitations and Biases](#risks-limitations-and-biases)
- [Training](#training)
- [Evaluation](#evaluation)
- [How to Get Started With the Model](#how-to-get-started-with-the-model)
# Model Detai... | [
-0.02601289376616478,
-0.013352490030229092,
-0.004063776694238186,
0.06844944506883621,
0.017918158322572708,
0.016773967072367668,
-0.007718529552221298,
-0.02069643698632717,
-0.014550870284438133,
0.052368227392435074,
-0.0058368840254843235,
-0.030540218576788902,
0.03400881960988045,
... |
Culmenus/opus-mt-de-is-finetuned-de-to-is_35g65cc | [] | 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 | ---
language: en
tags:
- exbert
license: apache-2.0
datasets:
- bookcorpus
- wikipedia
---
# BERT base model (uncased)
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1810.04805) and first released in
[this repository](http... | [
-0.0042279125191271305,
0.0030666447710245848,
-0.018318351358175278,
0.06348302215337753,
0.02924499846994877,
0.03182365372776985,
-0.019427748396992683,
-0.03530840948224068,
-0.028829434886574745,
0.049393828958272934,
0.017601648345589638,
-0.007109126076102257,
0.017407912760972977,
... |
Culmenus/opus-mt-de-is-finetuned-de-to-is_35g65cc_1 | [] | 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 | ---
language: en
tags:
- exbert
license: mit
datasets:
- bookcorpus
- wikipedia
---
# RoBERTa base model
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1907.11692) and first released in
[this repository](https://github.com... | [
-0.007590530440211296,
-0.004935127217322588,
-0.011219809763133526,
0.057838618755340576,
0.032035283744335175,
0.03816129267215729,
-0.02448303811252117,
-0.033550068736076355,
-0.03928845375776291,
0.05892898514866829,
0.02993435598909855,
-0.0075706494972109795,
0.0027749091386795044,
... |
Culmenus/opus-mt-de-is-finetuned-de-to-is_35g65cc_2 | [] | 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 | ---
language: zh
datasets: CLUECorpusSmall
widget:
- text: "这是很久之前的事情了"
---
# Chinese GPT2 Model
## Model description
The model is used to generate Chinese texts. You can download the model either from the [GPT2-Chinese Github page](https://github.com/Morizeyao/GPT2-Chinese), or via HuggingFace from the link [gp... | [
-0.02578655816614628,
-0.028309278190135956,
0.005375658627599478,
0.05093614384531975,
0.04364478960633278,
0.01380782201886177,
-0.013244430534541607,
-0.019305860623717308,
-0.01727347820997238,
0.053648050874471664,
-0.006007046438753605,
-0.012975327670574188,
0.008441193960607052,
0.... |
Culmenus/opus-mt-de-is-finetuned-de-to-is_ancc | [] | 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 | ---
language: en
---
This is a Hugging Face transformers-compatible conversion of the original dense 125M-parameter model from the paper "[Efficient Large Scale Language Modeling with Mixtures of Experts](https://arxiv.org/abs/2112.10684)" from Artetxe et al. Please refer to the original model card, which can be found ... | [
-0.04677199572324753,
-0.014479919336736202,
0.015567896887660027,
0.04151270538568497,
0.016734736040234566,
0.030734194442629814,
-0.023299286141991615,
-0.01256497297435999,
0.005334119312465191,
0.05355348065495491,
0.030285002663731575,
-0.007917664013803005,
0.03802492469549179,
0.01... |
Culmenus/opus-mt-de-is-finetuned-de-to-is_ekkicc | [] | 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 | ---
language: de
widget:
- text: "Heute ist sehr schönes Wetter in"
license: mit
---
# German GPT-2 model
In this repository we release (yet another) GPT-2 model, that was trained on various texts for German.
The model is meant to be an entry point for fine-tuning on other texts, and it is definitely not as good o... | [
-0.018749266862869263,
-0.020407073199748993,
0.01024685613811016,
0.05755780264735222,
0.012934335507452488,
0.033833108842372894,
-0.00794101133942604,
-0.010170923545956612,
-0.02067919820547104,
0.04466455429792404,
-0.013806273229420185,
-0.028332898393273354,
0.017702972516417503,
0.... |
Culmenus/opus-mt-de-is-finetuned-de-to-is_nr2-finetuned-de-to-is_nr2 | [] | 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 | ---
language: en
license: mit
---
# OpenAI GPT
## Table of Contents
- [Model Details](#model-details)
- [How To Get Started With the Model](#how-to-get-started-with-the-model)
- [Uses](#uses)
- [Risks, Limitations and Biases](#risks-limitations-and-biases)
- [Training](#training)
- [Evaluation](#evaluation)
- [Enviro... | [
-0.038806673139333725,
-0.013369699940085411,
-0.012141946703195572,
0.0409812368452549,
0.030795106664299965,
0.04759758710861206,
0.018059369176626205,
-0.006115547847002745,
-0.029736019670963287,
0.05112111568450928,
0.021771544590592384,
-0.004968271590769291,
0.013991916552186012,
0.... |
CuongLD/wav2vec2-large-xlsr-vietnamese | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"vi",
"dataset:common_voice, infore_25h",
"arxiv:2006.11477",
"arxiv:2006.13979",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"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 | https://wandb.ai/krohak/huggingface
https://huggingface.co/nandinib1999/quote-generator
https://github.com/nandinib1999/gpt2_quotes_generation/ | [
0.0014953877544030547,
-0.01666403003036976,
-0.026102682575583458,
0.048459816724061966,
0.04566483199596405,
0.024306857958436012,
-0.003411437850445509,
0.012621981091797352,
-0.04147995263338089,
0.05093854293227196,
-0.004490844905376434,
0.02124033309519291,
0.02527845837175846,
0.03... |
CurtisASmith/GPT-JRT | [] | 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
model-index:
- name: BERiT_7000
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. -->
# BERiT_7000
This model is a fin... | [
-0.01386423222720623,
-0.0016119831707328558,
-0.011387836188077927,
0.029579373076558113,
0.014719013124704361,
0.01706947572529316,
-0.01974128745496273,
-0.014880349859595299,
-0.04300210252404213,
0.052398305386304855,
0.017716718837618828,
-0.03849707171320915,
0.02104487642645836,
0.... |
CurtisBowser/DialoGPT-medium-sora-three | [] | 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
datasets:
- xtreme
metrics:
- f1
model-index:
- name: xlm-roberta-base-finetuned-panx-de
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: xtreme
type: xtreme
args: PAN-X.de
metrics:
- name:... | [
-0.02285177633166313,
-0.0029209493659436703,
0.006041921209543943,
0.020610405132174492,
0.029006201773881912,
0.025830013677477837,
-0.023114826530218124,
-0.009819703176617622,
-0.025708450004458427,
0.04948452487587929,
0.021983342245221138,
-0.04665680602192879,
0.009086270816624165,
... |
CurtisBowser/DialoGPT-small-sora | [
"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... | 7 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: bert-mlm-feedback-2021
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. -->
# bert-mlm-fee... | [
-0.02411532960832119,
0.0002418364747427404,
-0.02700049802660942,
0.04644516110420227,
0.0413532480597496,
0.019591782242059708,
-0.016643119975924492,
-0.023489290848374367,
-0.03228413686156273,
0.052625302225351334,
0.028224412351846695,
-0.03228553384542465,
0.0070421420969069,
0.0384... |
D3vil/DialoGPT-smaall-harrypotter | [] | 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
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
inference: false
extra_gated_prompt: |-
One more step before getting this model.
This model is open access and available to all, with a CreativeML OpenRAIL-M license further specifying rights and usage.
The Cr... | [
-0.002282333094626665,
0.0025574101600795984,
-0.02806631661951542,
0.020776471123099327,
0.024054497480392456,
0.021213166415691376,
0.010166371241211891,
-0.001197547186166048,
-0.018132926896214485,
0.04911166429519653,
0.02060457319021225,
-0.00903443992137909,
0.008735441602766514,
0.... |
D3xter1922/distilbert-base-uncased-finetuned-cola | [] | 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 | ---
language: en
thumbnail: https://github.com/borisdayma/huggingtweets/blob/master/img/logo.png?raw=true
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4... | [
0.009137587621808052,
-0.03549203649163246,
-0.0013966693077236414,
0.04406564310193062,
0.04815376549959183,
0.013190207071602345,
-0.024637939408421516,
-0.009416528977453709,
-0.03348304703831673,
0.03618267551064491,
-0.00627028476446867,
-0.00584224471822381,
0.0009775307262316346,
0.... |
D3xter1922/electra-base-discriminator-finetuned-cola | [
"pytorch",
"tensorboard",
"electra",
"text-classification",
"dataset:glue",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | {
"architectures": [
"ElectraForSequenceClassification"
],
"model_type": "electra",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"... | 68 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- squad
model-index:
- name: distilbert-base-uncased-finetuned-squad-ver5
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 ... | [
-0.022009344771504402,
-0.005798388738185167,
-0.031113075092434883,
0.049980685114860535,
0.062091369181871414,
0.023178011178970337,
-0.03030654601752758,
0.002055644989013672,
-0.035931650549173355,
0.050927236676216125,
0.03835871070623398,
-0.024185433983802795,
0.012945348396897316,
... |
DARKVIP3R/DialoGPT-medium-Anakin | [
"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... | 13 | null | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: BERiT_4500
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. -->
# BERiT_4500
This model is a fin... | [
-0.012826976366341114,
0.0003491960815154016,
-0.015402810648083687,
0.028939515352249146,
0.014563004486262798,
0.020293984562158585,
-0.02033376507461071,
-0.01930762641131878,
-0.04323219880461693,
0.049607280641794205,
0.016992010176181793,
-0.038821250200271606,
0.021512582898139954,
... |
DCU-NLP/bert-base-irish-cased-v1 | [
"pytorch",
"tf",
"bert",
"fill-mask",
"transformers",
"generated_from_keras_callback",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 1,244 | null | ---
language:
- "en"
tags:
- stable_diffusion
- Pokemon
- Eevee
- Umbreon
- Glaceon
- Vaporeon
- Espeon
- Jolteon
- Flareon
- Leafeon
- Eeveelutions
---
This model must be used with Stable Diffusion
This is version 1 of my model to generate Eeveelutions
Model download: https://huggingface.co/vgaggia/Eeveelutions/b... | [
-0.021827202290296555,
0.005215248558670282,
-0.008187752217054367,
0.0031282759737223387,
0.040303535759449005,
-0.00003928007572540082,
0.022744443267583847,
0.015624803490936756,
-0.043495889753103256,
0.04035119712352753,
0.02205481007695198,
-0.01701977476477623,
0.03745805472135544,
... |
DCU-NLP/electra-base-irish-cased-discriminator-v1 | [
"pytorch",
"electra",
"pretraining",
"ga",
"transformers",
"irish",
"license:apache-2.0"
] | null | {
"architectures": [
"ElectraForPreTraining"
],
"model_type": "electra",
"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 | ---
tags:
- generated_from_trainer
model-index:
- name: clip-roberta-finetuned
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. -->
# clip-roberta-finetuned
This mod... | [
-0.024896899238228798,
-0.008101684041321278,
-0.002907207002863288,
0.024039432406425476,
0.03635228052735329,
0.02347729727625847,
-0.02570587955415249,
-0.00849163718521595,
-0.04542626067996025,
0.058211419731378555,
0.03851311653852463,
-0.01831018552184105,
0.01869109459221363,
0.051... |
DCU-NLP/electra-base-irish-cased-generator-v1 | [
"pytorch",
"electra",
"fill-mask",
"ga",
"transformers",
"irish",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"ElectraForMaskedLM"
],
"model_type": "electra",
"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 | ---
license: mit
---
# NB-BERT fine-tuned on IMDB
## Description
This model is based on the pre-trained [NB-BERT-large model](https://huggingface.co/NbAiLab/nb-bert-large?text=P%C3%A5+biblioteket+kan+du+l%C3%A5ne+en+%5BMASK%5D.). It is a model for sentiment analysis. The idea behind this model was to check if a langu... | [
-0.007694491650909185,
-0.0024650294799357653,
0.003844289109110832,
0.057918064296245575,
0.029441095888614655,
0.03298410028219223,
-0.025025710463523865,
-0.016157235950231552,
-0.03453270345926285,
0.06487271189689636,
0.020742887631058693,
-0.0313514843583107,
0.025154341012239456,
0.... |
DHBaek/gpt2-stackoverflow-question-contents-generator | [
"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... | 14 | null | ---
language: en
thumbnail: http://www.huggingtweets.com/bradsprigg/1668030722213/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; widt... | [
0.0014065827708691359,
-0.030462447553873062,
-0.006827834527939558,
0.04782409220933914,
0.05597011744976044,
0.01702164299786091,
-0.013151020742952824,
-0.005220613908022642,
-0.04512646421790123,
0.04037700220942497,
0.02110430598258972,
0.007258625701069832,
-0.007080836221575737,
0.0... |
DHBaek/xlm-roberta-large-korquad-mask | [
"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,
... | 9 | null | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: BERiT_2000_enriched
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. -->
# BERiT_2000_enriched
T... | [
-0.0016742056468501687,
-0.009453460574150085,
-0.01651485450565815,
0.027805324643850327,
0.016701336950063705,
0.02173338457942009,
-0.020741453394293785,
-0.020780913531780243,
-0.03901509568095207,
0.05269930511713028,
0.023198582231998444,
-0.029931770637631416,
0.024349460378289223,
... |
DJSammy/bert-base-danish-uncased_BotXO-ai | [
"pytorch",
"jax",
"da",
"dataset:common_crawl",
"dataset:wikipedia",
"transformers",
"bert",
"masked-lm",
"license:cc-by-4.0",
"fill-mask"
] | fill-mask | {
"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... | 14 | null | ---
language: en
thumbnail: http://www.huggingtweets.com/wyld/1668032276555/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; width: 92p... | [
-0.0016119200736284256,
-0.03842645138502121,
-0.000875936180818826,
0.05516740307211876,
0.052071712911129,
0.012602230533957481,
-0.013538304716348648,
-0.00859917514026165,
-0.039191391319036484,
0.031776461750268936,
0.01414142269641161,
-0.00298027484677732,
-0.016822809353470802,
0.0... |
DJSammy/bert-base-swedish-uncased_BotXO-ai | [
"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... | 1 | null | ---
license: mit
---
### DevonM on Stable Diffusion
This is the `<DevonM>` 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... | [
-0.032497256994247437,
-0.018524084240198135,
-0.03026191145181656,
0.03868132084608078,
0.006362786516547203,
0.021223703399300575,
-0.0014574796659871936,
-0.007883901707828045,
-0.03554677590727806,
0.0431203655898571,
0.007275688461959362,
-0.010301632806658745,
0.033291105180978775,
0... |
DKpro000/DialoGPT-medium-harrypotter | [] | 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 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# {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 cluste... | [
-0.03682786226272583,
-0.017038146033883095,
-0.016540275886654854,
0.0510595329105854,
0.01117929257452488,
0.04447409510612488,
-0.01840854622423649,
-0.002739659510552883,
-0.070090651512146,
0.08364398777484894,
0.03946809098124504,
0.013144438154995441,
0.00234610796906054,
0.04092745... |
DSI/TweetBasedSA | [
"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... | 29 | null | ---
tags:
- conversational
---
# Dory DialoGPT Model | [
-0.053631559014320374,
0.016827883198857307,
0.02374865859746933,
0.027985455468297005,
0.02447638474404812,
0.00776805030182004,
-0.002683666069060564,
0.024116994813084602,
-0.013287165202200413,
0.016988808289170265,
0.0382453091442585,
-0.03726944327354431,
0.006736477836966515,
0.0324... |
DSI/ar_emotion_6 | [
"pytorch",
"bert",
"transformers"
] | null | {
"architectures": [
"BertForMultiLabelSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 1 | null | ---
language:
- en
license: creativeml-openrail-m
thumbnail: "https://huggingface.co/Guizmus/SD_PoW_Collection/resolve/main/showcase.jpg"
tags:
- stable-diffusion
- text-to-image
- image-to-image
library_name: "EveryDream"
inference: false
---
![PoW](https://huggingface.co/Guizmus/SD_PoW_Collection/resolve/main/141122... | [
-0.020458484068512917,
-0.015241841785609722,
-0.021993039175868034,
0.041841886937618256,
0.043902892619371414,
-0.003011616412550211,
0.02357938140630722,
-0.004949931986629963,
-0.032832227647304535,
0.042656756937503815,
0.03624953329563141,
0.005458194296807051,
0.0050918529741466045,
... |
DSI/human-directed-sentiment | [
"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... | 26 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
- f1
model-index:
- name: finetuning-sentiment-model-3000-samples
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
config: plain_text
... | [
-0.015083849430084229,
-0.010541161522269249,
-0.031249800696969032,
0.046042125672101974,
0.03627283126115799,
0.03720613941550255,
-0.019805103540420532,
-0.02097070775926113,
-0.037587255239486694,
0.06595782190561295,
0.045983973890542984,
-0.0185872670263052,
0.019736044108867645,
0.0... |
DTAI-KULeuven/mbert-corona-tweets-belgium-curfew-support | [
"pytorch",
"jax",
"bert",
"text-classification",
"multilingual",
"nl",
"fr",
"en",
"arxiv:2104.09947",
"transformers",
"Tweets",
"Sentiment analysis"
] | 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... | 29 | null | ---
license: bigscience-bloom-rail-1.0
language:
- ak
- ar
- as
- bm
- bn
- ca
- code
- en
- es
- eu
- fon
- fr
- gu
- hi
- id
- ig
- ki
- kn
- lg
- ln
- ml
- mr
- ne
- nso
- ny
- or
- pa
- pt
- rn
- rw
- sn
- st
- sw
- ta
- te
- tn
- ts
- tum
- tw
- ur
- vi
- wo
- xh
- yo
- zh
- zhs
- zht
- zu
pipeline_tag: text-gener... | [
-0.02328350953757763,
-0.00942818634212017,
0.0007412581471726298,
0.029513563960790634,
0.028732620179653168,
0.0005571389920078218,
0.002788001438602805,
-0.014607884921133518,
-0.03907816484570503,
0.05215369910001755,
0.02980920672416687,
-0.009952808730304241,
0.02128758281469345,
0.0... |
DTAI-KULeuven/robbertje-1-gb-bort | [
"pytorch",
"roberta",
"fill-mask",
"nl",
"dataset:oscar",
"dataset:oscar (NL)",
"dataset:dbrd",
"dataset:lassy-ud",
"dataset:europarl-mono",
"dataset:conll2002",
"arxiv:2101.05716",
"transformers",
"Dutch",
"Flemish",
"RoBERTa",
"RobBERT",
"RobBERTje",
"license:mit",
"autotrain_c... | 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... | 6 | null | ---
tags:
- image-classification
- timm
library_name: timm
license: apache-2.0
datasets:
- imagenet-12k
- laion-2b
---
# Model card for vit_base_patch16_clip_224.laion2b_ft_in12k
A Vision Transformer (ViT) image classification model. Pretrained on LAION-2B image-text pairs using OpenCLIP. Fine-tuned on ImageNet-12k in... | [
-0.025881243869662285,
-0.02826358564198017,
0.002057700650766492,
0.037044696509838104,
0.03242654353380203,
-0.00945857260376215,
-0.002775253728032112,
-0.009847210720181465,
-0.0037352205254137516,
0.05022662132978439,
0.022263122722506523,
0.00046985031804069877,
-0.003646640572696924,
... |
alexandrainst/da-emotion-classification-base | [
"pytorch",
"tf",
"bert",
"text-classification",
"da",
"transformers",
"license:cc-by-sa-4.0"
] | 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... | 837 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- wer
model-index:
- name: wav2vec2-xlsr-53-espeak-cv-ft-mhr2-ntsema-colab
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: audiofolder
type: audio... | [
-0.03127862140536308,
-0.002167951548472047,
-0.021796293556690216,
0.04394189640879631,
0.0425545834004879,
0.03767974674701691,
-0.012627225369215012,
-0.014736357145011425,
-0.023004112765192986,
0.061516173183918,
0.03520697355270386,
-0.019919874146580696,
0.007123188115656376,
0.0266... |
DaisyMak/bert-finetuned-squad-accelerate-10epoch_transformerfrozen | [
"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... | 1,907 | null | ---
license: creativeml-openrail-m
---
art by `caster_style` this style gives a lot of magical clothes, purple, and crystals, to prompts.
License This embedding is open access and available to all, with a CreativeML OpenRAIL-M license further specifying rights and usage. The CreativeML OpenRAIL License specifies:
You... | [
-0.03257882595062256,
0.0010995310731232166,
-0.01399711612612009,
0.022015085443854332,
0.05309988185763359,
0.01915154606103897,
-0.01868772692978382,
-0.000499273301102221,
-0.008005728013813496,
0.06434554606676102,
0.039057668298482895,
0.010673320852220058,
-0.0006017046398483217,
0.... |
Danih1502/t5-small-finetuned-en-to-de | [] | 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 | ---
language: en
license: apache-2.0
library_name: diffusers
tags: []
datasets: huggan/smithsonian_butterflies_subset
metrics: []
---
<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this com... | [
-0.030049344524741173,
-0.010801459662616253,
-0.005359895993024111,
0.035775311291217804,
0.01758579909801483,
0.01028935145586729,
0.009478244930505753,
-0.004802192561328411,
-0.007952499203383923,
0.05388458073139191,
0.00608182605355978,
-0.020918939262628555,
0.007096720859408379,
0.... |
DarkKibble/DialoGPT-medium-Tankman | [] | 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 | ---
language:
- ko # Example: fr
license: apache-2.0 # Example: apache-2.0 or any license from https://hf.co/docs/hub/repositories-licenses
library_name: kenlm # Optional. Example: keras or any library from https://github.com/huggingface/hub-docs/blob/main/js/src/lib/interfaces/Libraries.ts
tags:
- audio
- automatic... | [
-0.03196203336119652,
-0.018010517582297325,
0.012299871072173119,
0.0408945269882679,
0.03126189857721329,
0.025958089157938957,
0.00039788734284229577,
-0.0037277836818248034,
-0.0635683685541153,
0.06449544429779053,
-0.010631391778588295,
-0.024259988218545914,
0.009582134895026684,
0.... |
DarkWolf/kn-electra-small | [
"pytorch",
"electra",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "electra",
"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 | ---
language:
- ko # Example: fr
license: apache-2.0 # Example: apache-2.0 or any license from https://hf.co/docs/hub/repositories-licenses
library_name: kenlm # Optional. Example: keras or any library from https://github.com/huggingface/hub-docs/blob/main/js/src/lib/interfaces/Libraries.ts
tags:
- audio
- automatic... | [
-0.03355393186211586,
-0.02682214416563511,
0.01092677004635334,
0.03663359954953194,
0.032644979655742645,
0.016960885375738144,
-0.013347364962100983,
-0.012912295758724213,
-0.048634521663188934,
0.06523017585277557,
-0.003068796591833234,
-0.0285207349807024,
0.016435954719781876,
0.01... |
Darkrider/covidbert_medmarco | [
"pytorch",
"jax",
"bert",
"text-classification",
"arxiv:2010.05987",
"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... | 35 | null | ---
license: mit
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: deberta-base-finetuned-cola
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
config: cola
split: train
... | [
-0.027902834117412567,
-0.007509530521929264,
-0.00037181490915827453,
0.03362429514527321,
0.049450673162937164,
0.032946810126304626,
-0.025768207386136055,
-0.017013411968946457,
-0.052376531064510345,
0.057285625487565994,
0.041254088282585144,
-0.012172942981123924,
0.019535355269908905... |
Darkrider/covidbert_mednli | [
"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... | 3 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-finetuned-autoeval-test
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete... | [
-0.029692545533180237,
0.00679964292794466,
0.0014883262338116765,
0.031165380030870438,
0.03399050235748291,
0.008562485687434673,
-0.02029804326593876,
0.019733976572752,
-0.02120254747569561,
0.07670654356479645,
0.0093182772397995,
-0.01688799448311329,
0.01746952347457409,
0.030359352... |
DarshanDeshpande/marathi-distilbert | [
"pytorch",
"tf",
"distilbert",
"fill-mask",
"mr",
"dataset:Oscar Corpus, News, Stories",
"arxiv:1910.01108",
"transformers",
"license:apache-2.0",
"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... | 14 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-tr-colab
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 rem... | [
-0.04422087222337723,
-0.007171507924795151,
-0.027688486501574516,
0.03956277668476105,
0.05181502550840378,
0.031186401844024658,
-0.008198716677725315,
-0.004988147411495447,
-0.013067810796201229,
0.03925446793437004,
0.049849383533000946,
-0.01090935431420803,
0.00426359660923481,
0.0... |
DataikuNLP/distiluse-base-multilingual-cased-v1 | [
"pytorch",
"distilbert",
"arxiv:1908.10084",
"sentence-transformers",
"feature-extraction",
"sentence-similarity",
"transformers",
"license:apache-2.0"
] | sentence-similarity | {
"architectures": [
"DistilBertModel"
],
"model_type": "distilbert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngra... | 29 | null | Access to model munbatbai/gg is restricted and you are not in the authorized list. Visit https://huggingface.co/munbatbai/gg to ask for access. | [
-0.032375406473875046,
0.005059264600276947,
0.012718630023300648,
0.022409677505493164,
0.06440247595310211,
0.03295261040329933,
0.00874598789960146,
0.003964182920753956,
-0.046189308166503906,
0.0447898767888546,
0.05590413883328438,
-0.0022616777569055557,
0.028011107817292213,
0.0517... |
DataikuNLP/paraphrase-albert-small-v2 | [
"pytorch",
"albert",
"arxiv:1908.10084",
"sentence-transformers",
"feature-extraction",
"sentence-similarity",
"transformers",
"license:apache-2.0"
] | sentence-similarity | {
"architectures": [
"AlbertModel"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size":... | 628 | null | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: hcho22/opus-mt-ko-en-finetuned-en-to-kr
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. -... | [
-0.02373659797012806,
-0.019926918670535088,
0.020242027938365936,
0.01999211125075817,
0.040305063128471375,
-0.0024579039309173822,
-0.009517773054540157,
-0.004000733606517315,
-0.039496999233961105,
0.0542035773396492,
0.016054362058639526,
-0.020283639430999756,
0.02314588986337185,
0... |
DataikuNLP/paraphrase-multilingual-MiniLM-L12-v2 | [
"pytorch",
"bert",
"arxiv:1908.10084",
"sentence-transformers",
"feature-extraction",
"sentence-similarity",
"transformers",
"license:apache-2.0"
] | sentence-similarity | {
"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... | 1,517 | null | ---
license: creativeml-openrail-m
tags:
- text-to-image
---
To use it you have to use the word ''IconsMi'' in the prompt.
From my tests the images look better with this prompt:
highly detailed, trending on artstation, ios icon app, IconsMi
For negative prompts I got better results when I used: out of frame, dupl... | [
-0.0021792640909552574,
-0.026754194870591164,
-0.039791934192180634,
0.03205849975347519,
0.05614300072193146,
-0.001033565727993846,
-0.013980196788907051,
0.003962109796702862,
-0.006505179218947887,
0.04481898620724678,
0.044849902391433716,
-0.011355223134160042,
-0.01045185886323452,
... |
Davlan/bert-base-multilingual-cased-finetuned-hausa | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 151 | null | ---
license: creativeml-openrail-m
tags:
- text-to-image
---
# VoxelArt model V1
This is the fine-tuned Stable Diffusion model trained on Voxel Art images.
Use **VoxelArt** in your prompts.
### Sample images:
![voxelart.jpg](https://s3.amazonaws.com/moonup/production/uploads/1668056713800-635749860725c2f190a76e88.j... | [
-0.0069378637708723545,
-0.026744190603494644,
-0.015488766133785248,
0.03912939131259918,
0.03796561807394028,
0.015469081699848175,
0.0008190075750462711,
-0.01794632337987423,
-0.008773586712777615,
0.04876052960753441,
0.029964912682771683,
0.0009440455469302833,
-0.01051789615303278,
... |
Davlan/bert-base-multilingual-cased-finetuned-igbo | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 15 | null | ---
license: mit
---
### California Gurls music video on Stable Diffusion via Dreambooth trained on the [fast-DreamBooth.ipynb by TheLastBen](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/Dreambooth/fast_DreamBooth-Old-Method.ipynb#scrollTo=1pH1oP-7yBZm) & (https://colab.research.g... | [
-0.04461845010519028,
-0.027202686294913292,
-0.031647782772779465,
0.03900541737675667,
0.014559012837707996,
0.03170784190297127,
-0.00438880268484354,
0.011667247861623764,
-0.033804070204496384,
0.04133680835366249,
0.02106805518269539,
0.009624145925045013,
0.0013338152784854174,
0.02... |
Davlan/bert-base-multilingual-cased-finetuned-kinyarwanda | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 27 | null | https://civitai.com/models/25399/cardos-anime
https://civitai.com/models/24779/dark-sushi-mix-mix
https://civitai.com/models/21409/five-nuts-mixed-mix
https://civitai.com/models/23953/furnace-34
https://civitai.com/models/2583/hassaku-hentai-model
https://civitai.com/models/11866/meinapastel
https://civitai.com/m... | [
-0.004348041955381632,
-0.02978263795375824,
0.024222878739237785,
0.03976103663444519,
0.03160751983523369,
0.01587344892323017,
0.02144310437142849,
-0.009978877380490303,
-0.027187800034880638,
0.06459098309278488,
0.03784551844000816,
0.01037612184882164,
0.017142023891210556,
0.040784... |
Davlan/bert-base-multilingual-cased-finetuned-swahili | [
"pytorch",
"tf",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 67 | null | ---
language: en
datasets:
- Satellite-Instrument-NER
widget:
- text: "Centroid Moment Tensor Global Navigation Satellite System GNSS"
- text: "This paper describes the latest version of the algorithm MAIAC used for processing the MODIS Collection 6 data record."
- text: "We derive tropospheric column BrO during the AR... | [
-0.0475110188126564,
-0.0016427866648882627,
-0.017377901822328568,
0.02410217747092247,
0.04669249430298805,
0.023308729752898216,
-0.008666244335472584,
-0.030772889032959938,
-0.05118658393621445,
0.053044144064188004,
0.039708107709884644,
0.010110565461218357,
0.004742315970361233,
0.... |
Davlan/bert-base-multilingual-cased-masakhaner | [
"pytorch",
"tf",
"bert",
"token-classification",
"arxiv:2103.11811",
"transformers",
"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... | 88 | 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
... | [
-0.037023965269327164,
-0.0028895759023725986,
-0.005481247790157795,
0.025883199647068977,
0.045216936618089676,
-0.021539811044931412,
-0.0056975227780640125,
-0.02841464802622795,
-0.03295018523931503,
0.0666840523481369,
0.032926298677921295,
-0.02305501513183117,
0.02258586883544922,
... |
Davlan/byt5-base-eng-yor-mt | [
"pytorch",
"t5",
"text2text-generation",
"arxiv:2103.08647",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"T5ForConditionalGeneration"
],
"model_type": "t5",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_n... | 11 | null | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: amitjohn007/bert-finetuned-squad
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. -->
# a... | [
-0.03909405320882797,
-0.018426138907670975,
-0.013650989159941673,
0.03109346702694893,
0.030987631529569626,
0.024417616426944733,
-0.029457980766892433,
-0.0014135250821709633,
-0.03315429389476776,
0.041917551308870316,
0.013796822167932987,
-0.01091692689806223,
0.025848977267742157,
... |
Davlan/distilbert-base-multilingual-cased-ner-hrl | [
"pytorch",
"tf",
"distilbert",
"token-classification",
"transformers",
"autotrain_compatible",
"has_space"
] | 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,
... | 123,856 | null | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: minilm-finetuned-emotionclassification
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. -->
# min... | [
-0.02960837446153164,
-0.004242591094225645,
0.0008441319805569947,
0.03809588775038719,
0.04406294971704483,
0.03064451552927494,
-0.014795094728469849,
-0.01661089062690735,
-0.035597026348114014,
0.06093085929751396,
0.02760675549507141,
-0.034269899129867554,
0.029978077858686447,
0.03... |
Davlan/mT5_base_yoruba_adr | [
"pytorch",
"mt5",
"text2text-generation",
"arxiv:2003.10564",
"arxiv:2103.08647",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"MT5ForConditionalGeneration"
],
"model_type": "mt5",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 5 | null | ---
tags:
- FrozenLake-v1-4x4-no_slippery
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-FrozenLake-v1-4x4-noSlippery
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: FrozenLake-v1-4x4-no_slippery
type: Frozen... | [
-0.018624989315867424,
-0.017155196517705917,
-0.006220880895853043,
0.0328238345682621,
0.0511745885014534,
-0.020094001665711403,
-0.01242810022085905,
-0.011934482492506504,
-0.060836855322122574,
0.056670546531677246,
-0.00582740968093276,
-0.012293271720409393,
0.02155824936926365,
0.... |
Davlan/mbart50-large-yor-eng-mt | [
"pytorch",
"mbart",
"text2text-generation",
"arxiv:2103.08647",
"transformers",
"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... | 5 | 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: 7.56 +/- 2.71... | [
-0.021326197311282158,
-0.015406398102641106,
-0.007986919954419136,
0.0290406234562397,
0.046881772577762604,
-0.0015255992766469717,
-0.01878470554947853,
0.0026391425635665655,
-0.04043399170041084,
0.05579761043190956,
0.011174863204360008,
-0.012366489507257938,
0.01048499159514904,
0... |
Davlan/mt5-small-en-pcm | [
"pytorch",
"mt5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"MT5ForConditionalGeneration"
],
"model_type": "mt5",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 9 | null | ---
language:
- en
tags:
- stable-diffusion
- text-to-image
license: creativeml-openrail-m
inference: false
---
# Momocha mix models
Scrapped from [chenyfan's sharepoint](https://cyfan-my.sharepoint.com/:f:/g/personal/chenyfan_cyfan_onmicrosoft_com/EilOWB40m3ZJn6ahczIUIs4B6v0XvizO5YorOhG_5eYSUw?e=ZyP7qE)
Example outp... | [
-0.0076499744318425655,
-0.03377614915370941,
-0.003233616938814521,
0.034123558551073074,
0.03769512102007866,
0.0017168112099170685,
0.009423692710697651,
0.004846894647926092,
-0.022202687337994576,
0.05402519553899765,
0.030759932473301888,
-0.006676564924418926,
-0.011331637389957905,
... |
Davlan/mt5-small-pcm-en | [
"pytorch",
"mt5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"MT5ForConditionalGeneration"
],
"model_type": "mt5",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 9 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: distilbert-base-uncased-finetuned-cola
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
config: cola
... | [
-0.01747850328683853,
0.012832253240048885,
-0.02020123414695263,
0.042673300951719284,
0.06915391236543655,
0.023134620860219002,
-0.03030187264084816,
-0.027700090780854225,
-0.04639526456594467,
0.06051735207438469,
0.0334070548415184,
-0.010872622020542622,
0.021476954221725464,
0.0342... |
Davlan/mt5_base_yor_eng_mt | [
"pytorch",
"mt5",
"text2text-generation",
"arxiv:2103.08647",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"MT5ForConditionalGeneration"
],
"model_type": "mt5",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 8 | null | ---
tags:
- FrozenLake-v1-4x4-no_slippery
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-FrozenLake-v1-4x4-noSlippery
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: FrozenLake-v1-4x4-no_slippery
type: Frozen... | [
-0.01603703573346138,
-0.017346087843179703,
-0.006534783635288477,
0.031304776668548584,
0.048499420285224915,
-0.016299370676279068,
-0.012171256355941296,
-0.010308541357517242,
-0.058348529040813446,
0.05868718773126602,
-0.0022153547033667564,
-0.010398335754871368,
0.01870167814195156,... |
Davlan/xlm-roberta-base-finetuned-amharic | [
"pytorch",
"xlm-roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"XLMRobertaForMaskedLM"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repe... | 401 | null | ---
license: mit
---
### AnonV1 on Stable Diffusion via Dreambooth trained on the [fast-DreamBooth.ipynb by TheLastBen](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast-DreamBooth.ipynb) notebook
#### model by TheMindExpansionNetwork
This your the Stable Diffusion model fine-tune... | [
-0.044529832899570465,
-0.027181334793567657,
-0.019071368500590324,
0.029934296384453773,
0.020982032641768456,
0.007839903235435486,
0.011063767597079277,
0.0103857247158885,
-0.023239213973283768,
0.04348871484398842,
0.023188911378383636,
0.009182491339743137,
0.00624073063954711,
0.02... |
Davlan/xlm-roberta-base-finetuned-english | [
"pytorch",
"xlm-roberta",
"fill-mask",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"XLMRobertaForMaskedLM"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repe... | 5 | null | ---
language:
- ja
- ai
tags:
- translation
widget:
- text: "ari hawki = an konno"
example_title: "と 言う と "
---
| [
-0.01829427108168602,
-0.02578054554760456,
0.009749095886945724,
0.03314443305134773,
0.043814171105623245,
0.015020377933979034,
0.008162855170667171,
-0.012088888324797153,
-0.05140621215105057,
0.05427978187799454,
0.009027493186295033,
-0.01745641604065895,
0.01648062653839588,
0.0323... |
Davlan/xlm-roberta-base-finetuned-hausa | [
"pytorch",
"xlm-roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"XLMRobertaForMaskedLM"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repe... | 234 | null | ---
tags:
- generated_from_trainer
model-index:
- name: clip-l-roberta-finetuned
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. -->
# clip-l-roberta-finetuned
This... | [
-0.019698137417435646,
-0.0030727351550012827,
0.00024283993116114289,
0.022644542157649994,
0.037267833948135376,
0.01596805639564991,
-0.027268100529909134,
-0.0065709310583770275,
-0.045370589941740036,
0.053731441497802734,
0.03878592699766159,
-0.022087521851062775,
0.016678202897310257... |
Davlan/xlm-roberta-base-finetuned-igbo | [
"pytorch",
"xlm-roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"XLMRobertaForMaskedLM"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repe... | 68 | null | ---
language:
- en
tags:
- stable-diffusion
- text-to-image
license: mit
---
# Soft Brush Style Model / Dreambooth Training
This model is trained entirely on a collection of similar style images from varying sources
# Use
To use this model you have to download the .ckpt file as well as drop it into the "\stable-di... | [
-0.0026088841259479523,
-0.030736934393644333,
-0.005679910536855459,
0.03928482159972191,
0.026346324011683464,
0.010945106856524944,
0.003834047820419073,
0.013523929752409458,
-0.016922907903790474,
0.05356280878186226,
0.005530784372240305,
0.0004688014159910381,
-0.0063623846508562565,
... |
Davlan/xlm-roberta-base-finetuned-luo | [
"pytorch",
"xlm-roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"XLMRobertaForMaskedLM"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repe... | 5 | 2022-11-10T07:29:44Z | ---
library_name: Doc-UFCN
license: mit
tags:
- Doc-UFCN
- PyTorch
- Object detection
metrics:
- IoU
- F1
- AP@.5
- AP@.75
- AP@[.5,.95]
---
# Hugin-Munin line detection
The Hugin-Munin line detection model predicts text lines from Hugin-Munin document images. This model was developed during the [HUGIN-MUNIN project... | [
0.004853339865803719,
-0.03721978887915611,
-0.01500667817890644,
0.06647487729787827,
0.03317257761955261,
0.022361615672707558,
-0.021872030571103096,
-0.025077667087316513,
-0.016926314681768417,
0.03476331755518913,
0.01716662012040615,
0.007246063090860844,
0.00320261693559587,
0.0487... |
Davlan/xlm-roberta-base-finetuned-shona | [
"pytorch",
"xlm-roberta",
"fill-mask",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"XLMRobertaForMaskedLM"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repe... | 5 | 2022-11-10T07:40:43Z | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- squad
model-index:
- name: distilbert-base-uncased-finetuned-squad
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 remov... | [
-0.022321555763483047,
-0.0057744174264371395,
-0.030768074095249176,
0.05056020990014076,
0.0617896132171154,
0.023432329297065735,
-0.03157899156212807,
0.003995504230260849,
-0.03493516519665718,
0.05003051832318306,
0.03687223792076111,
-0.023609211668372154,
0.012196573428809643,
0.04... |
Davlan/xlm-roberta-base-finetuned-wolof | [
"pytorch",
"xlm-roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"XLMRobertaForMaskedLM"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repe... | 3 | null | ---
language:
- en
tags:
- stable-diffusion
- text-to-image
inference: false
---
# Cafe Unofficial Instagram TEST Model Release
> Trained on ~140k Instagram images made up of primarily Japanese accounts (mix of cosplay, model, and personal accounts)
> While the model can create some realistic Instagram-esque images o... | [
-0.0031670460011810064,
-0.03817135468125343,
-0.01930662989616394,
0.049129463732242584,
0.03867131099104881,
-0.01672286167740822,
-0.0036137267015874386,
0.004332876764237881,
-0.013343962840735912,
0.04223734140396118,
0.0368717685341835,
-0.0193378534168005,
-0.005797772668302059,
0.0... |
Davlan/xlm-roberta-base-finetuned-xhosa | [
"pytorch",
"xlm-roberta",
"fill-mask",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"XLMRobertaForMaskedLM"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repe... | 12 | null | ---
license: mit
tag: text-classification
widget:
- text: "Sehent hoerent oder lesent daß div chint, div bechoment von frowen Chvnegvnde Heinriches des Losen"
- text: "Mihály zágrábi püspök előtt Vaguth (dict.) László c. a püspöki várnépek (castrenses) Csázma comitatus-beli volt földjének egy részét, amelyet szolgálata... | [
0.0068816072307527065,
-0.03140566498041153,
-0.012632603757083416,
0.05867433175444603,
0.03780784085392952,
0.029509088024497032,
-0.002122803358361125,
0.01115558110177517,
-0.041719309985637665,
0.047609876841306686,
0.028827326372265816,
-0.024195585399866104,
-0.011307062581181526,
0... |
Davlan/xlm-roberta-base-finetuned-yoruba | [
"pytorch",
"xlm-roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"XLMRobertaForMaskedLM"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repe... | 29 | null | ---
tags:
- image-classification
- timm
library_name: timm
license: apache-2.0
datasets:
- imagenet-1k
- wit-400m
---
# Model card for vit_base_patch32_clip_224.openai_ft_in1k
A Vision Transformer (ViT) image classification model. Pretrained on WIT-400M image-text pairs by OpenAI using CLIP. Fine-tuned on ImageNet-1k ... | [
-0.028764866292476654,
-0.025369709357619286,
0.002976805903017521,
0.03715283051133156,
0.03436495363712311,
-0.001999237108975649,
-0.0012997639132663608,
-0.00331176002509892,
0.001704408205114305,
0.05266505852341652,
0.02371138706803322,
-0.0007651904597878456,
-0.006235336884856224,
... |
Davlan/xlm-roberta-base-masakhaner | [
"pytorch",
"xlm-roberta",
"token-classification",
"arxiv:2103.11811",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"XLMRobertaForTokenClassification"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 3 | null | ---
license: cc-by-nc-4.0
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: NLLB-alt-cv-bleu-40
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. -->
... | [
-0.013933494687080383,
0.005472557619214058,
-0.017113422974944115,
0.0315689817070961,
0.03992428258061409,
-0.002996636787429452,
-0.021447403356432915,
-0.02109726145863533,
-0.02241125889122486,
0.045387741178274155,
0.020945457741618156,
-0.02557186782360077,
-0.0028593738097697496,
0... |
Davlan/xlm-roberta-base-wikiann-ner | [
"pytorch",
"tf",
"xlm-roberta",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"XLMRobertaForTokenClassification"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 235 | null | ---
license: mit
---
### Solo Levelling Art Style on Stable Diffusion via Dreambooth trained on the [fast-DreamBooth.ipynb by TheLastBen](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast-DreamBooth.ipynb) notebook
#### model by Classacre
This your the Stable Diffusion model fine-... | [
-0.02038591168820858,
-0.020817957818508148,
-0.016180241480469704,
0.03325102850794792,
0.02741989679634571,
0.02611074410378933,
0.003810424590483308,
0.008352202363312244,
-0.024485189467668533,
0.04319857805967331,
0.016794530674815178,
-0.008345365524291992,
-0.00015171222912613302,
0... |
Davlan/xlm-roberta-large-masakhaner | [
"pytorch",
"tf",
"xlm-roberta",
"token-classification",
"arxiv:2103.11811",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"XLMRobertaForTokenClassification"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 1,449 | null | # Introduction
Models in this file are downloaded from
<https://github.com/wenet-e2e/wenet/releases/download/v2.0.1/en.tar.gz>
```bash
wget https://github.com/wenet-e2e/wenet/releases/download/v2.0.1/en.tar.gz
tar xvf en.tar.gz --strip-components=1
rm en.tar.gz
```
| [
-0.030202049762010574,
-0.012991839088499546,
-0.0068403566256165504,
-0.01635824702680111,
0.038099680095911026,
0.03530829772353172,
-0.013128325343132019,
0.029876865446567535,
-0.035845231264829636,
0.04613783210515976,
0.03588053956627846,
0.02016550488770008,
0.04427950829267502,
0.0... |
Davlan/xlm-roberta-large-ner-hrl | [
"pytorch",
"tf",
"xlm-roberta",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"XLMRobertaForTokenClassification"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 1,322 | null | Access to model multimodalart/extra_gated_heading is restricted and you are not in the authorized list. Visit https://huggingface.co/multimodalart/extra_gated_heading to ask for access. | [
-0.04546864330768585,
-0.0050096963532269,
0.015562471933662891,
0.010233141481876373,
0.03984948620200157,
0.03199365362524986,
-0.011335086077451706,
-0.0328410267829895,
-0.01205467525869608,
0.03789933770895004,
0.02906990423798561,
-0.013259893283247948,
0.03430424630641937,
0.0470876... |
Dawn576/Dawn | [] | 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:
- CartPole-v1
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: Reinforce-cartpole0001
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: CartPole-v1
type: CartPole-v1
metrics:
- type... | [
-0.02913668006658554,
0.021093320101499557,
0.00330199021846056,
0.010330055840313435,
0.04285695031285286,
-0.01794859766960144,
-0.026332024484872818,
-0.016654284670948982,
-0.029849490150809288,
0.0844055637717247,
0.017666906118392944,
-0.005708435084670782,
0.01463544275611639,
0.018... |
Daymarebait/Discord_BOT_RICK | [
"conversational"
] | conversational | {
"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... | 3 | null | ---
language:
- es
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- facebook/multilingual_librispeech
metrics:
- wer
model-index:
- name: Whisper Small Es - Sanchit Gandhi
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
datase... | [
-0.008362953551113605,
-0.005282498896121979,
-0.021602317690849304,
0.0453854501247406,
0.04290506988763809,
0.030453767627477646,
-0.023438679054379463,
-0.0008407621062360704,
-0.03932078927755356,
0.07505913078784943,
0.034154754132032394,
-0.014548972249031067,
0.011485844850540161,
0... |
Dayout/test | [] | 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: openrail
---
<h3 align="center">PDF Paragraphs Extraction</h3>
<p align="center">A model for extracting paragraphs from PDFs</p>
This model uses features from the PDF to extract the text and paragraphs from it. It can be used as a service.
The paragraphs contain the page number, the position in the pa... | [
-0.013379229232668877,
-0.05046022683382034,
-0.019580740481615067,
0.013780917041003704,
0.0540362186729908,
0.03260686248540878,
-0.013503937982022762,
-0.007020572200417519,
-0.05122675374150276,
0.06292178481817245,
0.05422399938106537,
0.027605842798948288,
0.024104420095682144,
0.029... |
Dazai/Ko | [] | 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
---
### tyxxxszv on Stable Diffusion via Dreambooth trained on the [fast-DreamBooth.ipynb by TheLastBen](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast-DreamBooth.ipynb) notebook
#### model by sorupopic
This your the Stable Diffusion model fine-tuned the tyxxxs... | [
-0.03535119816660881,
-0.022232625633478165,
-0.01581999473273754,
0.02950766496360302,
0.013780671171844006,
0.020861057564616203,
-0.0020740688778460026,
0.0035766558721661568,
-0.03310050815343857,
0.033842865377664566,
0.021536560729146004,
0.001150196185335517,
-0.0041166869923472404,
... |
Dazai/Ok | [] | 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
---
# NB-BERT fine-tuned on NoReC
## Description
This model is based on the pre-trained [NB-BERT-large model](https://huggingface.co/NbAiLab/nb-bert-large?text=P%C3%A5+biblioteket+kan+du+l%C3%A5ne+en+%5BMASK%5D.). It is a model for sentiment analysis.
## Data for fine-tuning
This model was fine-tu... | [
-0.002811403013765812,
0.0011929062893614173,
0.008219237439334393,
0.05517743155360222,
0.029764391481876373,
0.02711995132267475,
-0.01646473817527294,
-0.019708268344402313,
-0.04254916310310364,
0.061387479305267334,
0.0252250824123621,
-0.032975099980831146,
0.04779164865612984,
0.041... |
Dbluciferm3737/Idk | [] | 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
... | [
-0.03736313059926033,
-0.0025568341370671988,
-0.005114344414323568,
0.02509385533630848,
0.04561987519264221,
-0.02074156329035759,
-0.005460276734083891,
-0.027295971289277077,
-0.03299909457564354,
0.0658092275261879,
0.032171640545129776,
-0.023224836215376854,
0.022976446896791458,
0.... |
Ddarkros/Test | [] | 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 | # Introduction
This repo contains torchscript models for Wav2Vec 2.0.
| [
-0.046047672629356384,
-0.035357702523469925,
0.004369454924017191,
0.031310707330703735,
0.03589422628283501,
0.014270744286477566,
-0.0022423178888857365,
0.022191867232322693,
-0.0033077208790928125,
0.022600434720516205,
0.07465467602014542,
0.017003027722239494,
0.006440464872866869,
... |
DeadBeast/roberta-base-pretrained-mr-2 | [
"pytorch",
"jax",
"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... | 5 | null | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
widget:
source_sentence: "亚丝娜"
sentences:
- "火影忍者"
- "Sword Art Online"
- "结城明日奈"
- "アスナ"
---
# ACGVoc2vec
结构为[sentence-transformers](https://github.com/UKPLab/sentence-transformers)，使用其... | [
-0.01883375085890293,
-0.0261071790009737,
-0.006664224434643984,
0.06463310122489929,
0.023135246708989143,
0.03170645982027054,
-0.004718378186225891,
0.0010676896199584007,
-0.06727711856365204,
0.08363877236843109,
0.03268378600478172,
0.015804775059223175,
0.0035182724241167307,
0.033... |
Declan/Breitbart_model_v2 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 7 | null | ---
tags:
- generated_from_trainer
model-index:
- name: SciBERT-WIKI_Life_Form_Finetuned
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. -->
# SciBERT-WIKI_Life_Form... | [
-0.02843162976205349,
-0.026566816493868828,
-0.02409372106194496,
0.020250121131539345,
0.028987562283873558,
0.029261386021971703,
-0.021876635029911995,
-0.011821703054010868,
-0.05401267856359482,
0.06377643346786499,
0.059665217995643616,
-0.005554540082812309,
0.03062746487557888,
0.... |
Declan/Breitbart_model_v4 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 3 | null | ---
language:
- es
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- facebook/multilingual_librispeech
metrics:
- wer
model-index:
- name: Whisper Small Es - Sanchit Gandhi
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
datase... | [
-0.008553744293749332,
-0.006078295409679413,
-0.02141796424984932,
0.04547988623380661,
0.0437687449157238,
0.030140917748212814,
-0.022779027000069618,
-0.0002837607462424785,
-0.03919536620378494,
0.07497645914554596,
0.03405054286122322,
-0.014570409432053566,
0.010769284330308437,
0.0... |
Declan/Breitbart_model_v5 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 3 | null | ---
tags:
- Pixelcopter-PLE-v0
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: Reinforce-pixelcopter0001
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Pixelcopter-PLE-v0
type: Pixelcopter-PLE-v0... | [
-0.040980659425258636,
0.015965064987540245,
0.013063471764326096,
0.01861170306801796,
0.049553222954273224,
-0.013872718438506126,
-0.02038000337779522,
-0.02487708255648613,
-0.016905806958675385,
0.06816748529672623,
0.03677848353981972,
-0.008557452820241451,
0.01294889859855175,
-0.0... |
Declan/ChicagoTribune_model_v8 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 7 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- gsm8k
model-index:
- name: flan-t5-xl-finetuned-gsm8k
results: []
widget:
- "Please, answer the following question reasoning step-by-step: If Manu eats twice a day, how many meals does he take for a week?"
---
<!-- This model card has been generat... | [
0.002029708120971918,
0.0026078771334141493,
0.002385859377682209,
0.04207564890384674,
0.012718231417238712,
0.007409653626382351,
-0.008057846687734127,
-0.006350092124193907,
-0.014055633917450905,
0.030532963573932648,
0.03259682282805443,
-0.020666498690843582,
0.0232292041182518,
0.0... |
Declan/FoxNews_model_v2 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 3 | null | ---
license: mit
tags:
- generated_from_trainer
datasets:
- xtreme
metrics:
- f1
model-index:
- name: xlm-roberta-base-finetuned-panx-de
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: xtreme
type: xtreme
config: PAN-X.de
split: train
... | [
-0.026058118790388107,
-0.0032153239008039236,
0.006586355157196522,
0.019598715007305145,
0.02867300994694233,
0.02619035914540291,
-0.02432839386165142,
-0.011230822652578354,
-0.023699644953012466,
0.05015382915735245,
0.021521132439374924,
-0.04274734854698181,
0.009252239018678665,
0.... |
Declan/HuffPost_model_v2 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 3 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- xsum
metrics:
- rouge
model-index:
- name: t5-small-finetuned-xsum
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: xsum
type: xsum
config: default
split:... | [
-0.006019387394189835,
-0.007969468832015991,
0.006921845953911543,
0.036187414079904556,
0.033685144037008286,
0.0016374816186726093,
-0.030962064862251282,
-0.02830721251666546,
-0.030963938683271408,
0.051067885011434555,
0.024361932650208473,
-0.01606982946395874,
-0.010129140689969063,
... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.