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
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51
438k
embedding
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AmirBialer/amirbialer-Classifier
[]
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 datasets: - samsum model-index: - name: pegasus-samsum 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. --> # pegasus-samsum This ...
[ -0.03537223860621452, -0.009995458647608757, -0.009078354574739933, 0.0336327999830246, 0.047484416514635086, 0.02016928233206272, 0.0011803862871602178, -0.018250370398163795, -0.04286808893084526, 0.06861580908298492, 0.03248583897948265, -0.015117138624191284, 0.012669446878135204, 0.03...
AmirHussein/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: apache-2.0 tags: - generated_from_trainer datasets: - lextreme metrics: - precision - recall - f1 - accuracy model-index: - name: distilbert-base-multilingual-cased-mapa_fine-ner results: - task: name: Token Classification type: token-classification dataset: name: lextreme t...
[ -0.0006481674499809742, 0.004478667862713337, -0.02032092958688736, 0.052863359451293945, 0.04241395741701126, 0.015785664319992065, -0.013588294386863708, -0.04286302626132965, -0.04820975661277771, 0.06166631728410721, 0.021004067733883858, -0.03556035831570625, 0.020449334755539894, 0.0...
Amirosein/roberta
[ "pytorch", "roberta", "fill-mask", "transformers", "autotrain_compatible" ]
fill-mask
{ "architectures": [ "RobertaForMaskedLM" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngra...
6
null
--- language: - en library_name: diffusers tags: - stable-diffusion - lora --- # Model Card for svjack/concept-caption-3m-sd-lora-en ## Installation ```bash pip install -U diffusers pip install transformers ``` ## Usage ```python from diffusers import StableDiffusionPipeline import torch pipe = StableDiffusionPip...
[ -0.02667335607111454, -0.0006886730552650988, 0.0035675745457410812, 0.04455830901861191, 0.035592276602983475, 0.016889212653040886, -0.0076049333438277245, -0.016021965071558952, -0.035663947463035583, 0.06910428404808044, -0.0070054554380476475, -0.023058531805872917, 0.014438612386584282...
Analufm/Ana
[]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
2023-03-20T08:42:55Z
--- tags: - Pixelcopter-PLE-v0 - reinforce - reinforcement-learning - custom-implementation - deep-rl-class model-index: - name: Reinforce-Pixelcopter-PLE-v0 results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: Pixelcopter-PLE-v0 type: Pixelcopter-PLE...
[ -0.039976634085178375, 0.015688035637140274, 0.014176183380186558, 0.017613200470805168, 0.04948504641652107, -0.013645753264427185, -0.019185297191143036, -0.02402604930102825, -0.017719894647598267, 0.06756393611431122, 0.03554423153400421, -0.00816679559648037, 0.010942128486931324, -0....
Anamika/autonlp-fa-473312409
[ "pytorch", "roberta", "text-classification", "en", "dataset:Anamika/autonlp-data-fa", "transformers", "autonlp", "co2_eq_emissions" ]
text-classification
{ "architectures": [ "RobertaForSequenceClassification" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "...
35
null
--- tags: - generated_from_trainer datasets: - funsd model-index: - name: layoutlm-funsd 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. --> # layoutlm-funsd This m...
[ -0.017815181985497475, 0.009775682352483273, 0.00014544726582244039, 0.04327036440372467, 0.011642207391560078, 0.02174214832484722, 0.00009574738214723766, -0.029769133776426315, -0.04234251379966736, 0.034805379807949066, 0.03173745796084404, -0.024220144376158714, 0.010375451296567917, ...
Andi/bert-tt-ner-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
--- tags: - generated_from_trainer metrics: - accuracy model-index: - name: test_model 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. --> # test_model This model i...
[ -0.03553437814116478, -0.022867364808917046, -0.013759920373558998, 0.05191945284605026, 0.038339436054229736, 0.015232693403959274, -0.00889695156365633, -0.019305657595396042, -0.055798448622226715, 0.05901718884706497, 0.016106775030493736, -0.025741051882505417, 0.008712302893400192, 0...
Andrija/M-bert-NER
[ "pytorch", "bert", "token-classification", "hr", "sr", "multilingual", "dataset:hr500k", "transformers", "license:apache-2.0", "autotrain_compatible" ]
token-classification
{ "architectures": [ "BertForTokenClassification" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat...
8
null
--- tags: - conversational --- # Basil from OMORI Model
[ -0.03351661190390587, 0.007610642351210117, 0.021815458312630653, 0.010343587957322598, 0.0026167994365096092, -0.0035556317307054996, 0.007824418134987354, 0.028985965996980667, -0.01752219907939434, 0.03589857369661331, 0.04473697766661644, -0.02238788641989231, 0.02661026082932949, 0.02...
Anirbanbhk/Hate-speech-Pretrained-movies
[ "tf", "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...
20
null
--- library_name: stable-baselines3 tags: - PandaReachDense-v2 - deep-reinforcement-learning - reinforcement-learning - stable-baselines3 model-index: - name: A2C results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: PandaReachDense-v2 type: PandaReach...
[ -0.049620166420936584, -0.016052553430199623, -0.00874309055507183, 0.03634137287735939, 0.04113032668828964, 0.0031584480311721563, -0.021237313747406006, -0.010262164287269115, -0.03796762600541115, 0.056824691593647, 0.02428234927356243, -0.003060367191210389, 0.032189641147851944, 0.00...
Anomic/DialoGPT-medium-loki
[]
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: ml-agents tags: - SnowballTarget - deep-reinforcement-learning - reinforcement-learning - ML-Agents-SnowballTarget --- # **ppo** Agent playing **SnowballTarget** This is a trained model of a **ppo** agent playing **SnowballTarget** using the [Unity ML-Agents Library](https://github.com/Unity-Tech...
[ -0.029043935239315033, -0.004678237717598677, -0.017174825072288513, 0.0522172786295414, 0.036681972444057465, 0.026492943987250328, -0.0007505264948122203, -0.035555414855480194, -0.02597406506538391, 0.0460902638733387, 0.024869153276085854, -0.00908694602549076, 0.01817370392382145, 0.0...
AnonymousSub/SR_rule_based_roberta_hier_triplet_epochs_1_shard_1
[ "pytorch", "roberta", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "RobertaModel" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
1
null
--- license: mit datasets: - competitions/aiornot language: - en metrics: - accuracy tags: - classification - computer vision --- ## Usage: Follow the following code example to use this model. ```python # import libraries from transformers import AutoModel, AutoModelForImageClassification import torch from datasets im...
[ -0.030718257650732994, -0.024662762880325317, -0.012102757580578327, 0.02669297344982624, 0.05125971511006355, -0.013945969752967358, -0.01367106195539236, -0.020457303151488304, -0.030421467497944832, 0.05161133036017418, 0.01858932338654995, 0.019496535882353783, -0.0082879438996315, 0.0...
AnonymousSub/SR_rule_based_roberta_twostage_quadruplet_epochs_1_shard_10
[ "pytorch", "roberta", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "RobertaModel" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
8
2023-03-20T10:51:56Z
--- license: mit tags: - generated_from_trainer datasets: - lextreme metrics: - precision - recall - f1 - accuracy model-index: - name: roberta-base-mapa_fine-ner results: - task: name: Token Classification type: token-classification dataset: name: lextreme type: lextreme config: m...
[ -0.013712605461478233, 0.0033270197454839945, 0.011514337733387947, 0.019034549593925476, 0.02296878956258297, 0.016617370769381523, -0.027219032868742943, -0.026877233758568764, -0.03944653645157814, 0.042596038430929184, 0.02688879892230034, -0.03135594353079796, 0.017666446045041084, 0....
AnonymousSub/SR_rule_based_roberta_twostagequadruplet_hier_epochs_1_shard_10
[ "pytorch", "roberta", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "RobertaModel" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
4
null
--- library_name: ml-agents tags: - SnowballTarget - deep-reinforcement-learning - reinforcement-learning - ML-Agents-SnowballTarget --- # **ppo** Agent playing **SnowballTarget** This is a trained model of a **ppo** agent playing **SnowballTarget** using the [Unity ML-Agents Library](https://github.com/Unity-Tech...
[ -0.029752839356660843, -0.005289151798933744, -0.017361851409077644, 0.052012402564287186, 0.03551148250699043, 0.02613949589431286, -0.0015889115165919065, -0.03435351327061653, -0.024745529517531395, 0.04597119241952896, 0.025577383115887642, -0.009326169267296791, 0.018536457791924477, ...
AnonymousSub/SR_rule_based_roberta_twostagetriplet_epochs_1_shard_10
[ "pytorch", "roberta", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "RobertaModel" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
4
null
--- license: apache-2.0 tags: - generated_from_trainer metrics: - rouge - bleu model-index: - name: Salesforce-codet5-small-CodeXGLUE-CONCODE-adamw results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete ...
[ -0.007906481623649597, 0.0043115983717143536, -0.012074731290340424, 0.01487293653190136, 0.06374141573905945, 0.020114509388804436, -0.031508319079875946, -0.0029256369452923536, -0.016992835327982903, 0.0587223619222641, 0.007660774048417807, -0.006600948981940746, 0.0016998705687001348, ...
AnonymousSub/SR_rule_based_roberta_twostagetriplet_hier_epochs_1_shard_1
[ "pytorch", "roberta", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "RobertaModel" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
4
2023-03-20T10:56:11Z
# `vocabtrimmer/xlm-roberta-base-trimmed-pt-15000-tweet-sentiment-pt` This model is a fine-tuned version of [/home/asahi/lm-vocab-trimmer/ckpts/xlm-roberta-base-trimmed-pt-15000](https://huggingface.co//home/asahi/lm-vocab-trimmer/ckpts/xlm-roberta-base-trimmed-pt-15000) on the [cardiffnlp/tweet_sentiment_multilingua...
[ -0.01825442723929882, -0.02960878610610962, -0.0018230224959552288, 0.025355491787195206, 0.03377512842416763, 0.02529122307896614, -0.006214332301169634, -0.016641125082969666, -0.04701143503189087, 0.03949590399861336, 0.020780295133590698, -0.055292531847953796, -0.025280781090259552, 0...
AnonymousSub/SR_rule_based_roberta_twostagetriplet_hier_epochs_1_shard_10
[ "pytorch", "roberta", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "RobertaModel" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
7
null
--- library_name: ml-agents tags: - SnowballTarget - deep-reinforcement-learning - reinforcement-learning - ML-Agents-SnowballTarget --- # **ppo** Agent playing **SnowballTarget** This is a trained model of a **ppo** agent playing **SnowballTarget** using the [Unity ML-Agents Library](https://github.com/Unity-Tech...
[ -0.029599914327263832, -0.006073490250855684, -0.0174200888723135, 0.052212830632925034, 0.035520412027835846, 0.02488762140274048, -0.0025384624022990465, -0.03581985831260681, -0.02643277868628502, 0.04647365212440491, 0.028005335479974747, -0.006981347221881151, 0.018161101266741753, 0....
AnonymousSub/SR_rule_based_twostagetriplet_epochs_1_shard_1
[ "pytorch", "bert", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "BertModel" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": nul...
2
null
--- license: cc-by-4.0 metrics: - bleu4 - meteor - rouge-l - bertscore - moverscore language: ko datasets: - lmqg/qg_koquad pipeline_tag: text2text-generation tags: - question answering widget: - text: "question: 매드 클라운이 참가해 큰 화제를 모았던 프로그램은?, context: 과거 소울 컴퍼니 소속으로 소울 컴퍼니 해체 후 현재의 소속사는 스타쉽 엑스이다. Mad Clown vs Crucial ...
[ 0.017133494839072227, -0.020531509071588516, -0.0017524416325613856, 0.024444304406642914, 0.03006364032626152, -0.00047384746721945703, -0.008523308672010899, 0.013321743346750736, -0.054693035781383514, 0.036968957632780075, 0.025177888572216034, 0.0005690544494427741, 0.02078486792743206,...
AnonymousSub/SR_rule_based_twostagetriplet_hier_epochs_1_shard_1
[ "pytorch", "bert", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "BertModel" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": nul...
2
2023-03-20T11:10:46Z
--- tags: - Pixelcopter-PLE-v0 - reinforce - reinforcement-learning - custom-implementation - deep-rl-class model-index: - name: pixelcopter results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: Pixelcopter-PLE-v0 type: Pixelcopter-PLE-v0 metrics: ...
[ -0.04243086650967598, 0.014135081321001053, 0.014599905349314213, 0.019513022154569626, 0.049128733575344086, -0.013454117812216282, -0.019227920100092888, -0.02969479374587536, -0.01656840182840824, 0.06584187597036362, 0.037262070924043655, -0.006947703193873167, 0.008714687079191208, -0...
AnonymousSub/bert_triplet_epochs_1_shard_10
[ "pytorch", "bert", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "BertModel" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": nul...
1
null
--- tags: - generated_from_trainer metrics: - accuracy - precision - recall model-index: - name: MarBERT-finetuned-CrossVal-fnd 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...
[ -0.011636442504823208, -0.003213196760043502, -0.0026686841156333685, 0.02962731011211872, 0.03324511647224426, 0.018717486411333084, -0.02774728275835514, -0.014593622647225857, -0.027916740626096725, 0.058333996683359146, 0.03166970983147621, -0.03497426584362984, 0.02287682145833969, 0....
AnonymousSub/cline-emanuals-s10-AR
[ "pytorch", "roberta", "text-classification", "transformers" ]
text-classification
{ "architectures": [ "RobertaForSequenceClassification" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "...
27
null
--- tags: - generated_from_trainer datasets: - inglish metrics: - bleu model-index: - name: opus-mt-en-id-jakarta results: - task: name: Sequence-to-sequence Language Modeling type: text2text-generation dataset: name: inglish type: inglish config: default split: validation ...
[ -0.00838952511548996, -0.008780308067798615, -0.0036609023809432983, 0.03881562873721123, 0.02718195505440235, 0.003943474963307381, 0.000597851409111172, -0.02171861194074154, -0.022836832329630852, 0.07124990969896317, 0.004293943289667368, -0.034170832484960556, -0.02605266496539116, 0....
AnonymousSub/cline-emanuals-s10-SR
[]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
null
--- tags: - generated_from_trainer datasets: - inglish metrics: - bleu model-index: - name: opus-mt-id-en-jakarta results: - task: name: Sequence-to-sequence Language Modeling type: text2text-generation dataset: name: inglish type: inglish config: default split: validation ...
[ -0.008251292631030083, -0.00928856898099184, -0.002964914543554187, 0.036859218031167984, 0.027058100327849388, 0.0037745526060462, 0.00017069057503249496, -0.021966204047203064, -0.02168373391032219, 0.07050401717424393, 0.0048046051524579525, -0.033743079751729965, -0.024923870339989662, ...
AnonymousSub/cline-emanuals-techqa
[ "pytorch", "roberta", "question-answering", "transformers", "autotrain_compatible" ]
question-answering
{ "architectures": [ "RobertaForQuestionAnswering" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_re...
4
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...
AnonymousSub/cline-techqa
[ "pytorch", "roberta", "question-answering", "transformers", "autotrain_compatible" ]
question-answering
{ "architectures": [ "RobertaForQuestionAnswering" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_re...
6
null
--- license: apache-2.0 --- A differenced model extracted from https://huggingface.co/georgefen/Face-Landmark-ControlNet.
[ -0.03989294916391373, -0.00106545421294868, 0.0058202845975756645, -0.002080196049064398, 0.020246531814336777, 0.004363067913800478, -0.012188268825411797, 0.007786959409713745, -0.01106377225369215, 0.05608142539858818, 0.021066024899482727, -0.0007224874570965767, 0.034280240535736084, ...
AnonymousSub/cline
[ "pytorch", "roberta", "transformers" ]
null
{ "architectures": [ "LecbertForPreTraining" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_n...
2
null
--- library_name: stable-baselines3 tags: - SpaceInvadersNoFrameskip-v4 - deep-reinforcement-learning - reinforcement-learning - stable-baselines3 model-index: - name: DQN results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: SpaceInvadersNoFrameskip-v4 ...
[ -0.03879804536700249, -0.0165538527071476, -0.01568060927093029, 0.03672200068831444, 0.0491131991147995, -0.005142222158610821, -0.015390818938612938, -0.02419053576886654, -0.029738379642367363, 0.053463973104953766, 0.02221616357564926, -0.03048289194703102, 0.017853451892733574, 0.0149...
AnonymousSub/cline_emanuals
[ "pytorch", "roberta", "transformers" ]
null
{ "architectures": [ "LecbertForPreTraining" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_n...
3
null
# `vocabtrimmer/xlm-roberta-base-trimmed-it-60000-tweet-sentiment-it` This model is a fine-tuned version of [/home/asahi/lm-vocab-trimmer/ckpts/xlm-roberta-base-trimmed-it-60000](https://huggingface.co//home/asahi/lm-vocab-trimmer/ckpts/xlm-roberta-base-trimmed-it-60000) on the [cardiffnlp/tweet_sentiment_multilingua...
[ -0.01090895663946867, -0.02131861075758934, -0.003578984411433339, 0.013497347012162209, 0.027829525992274284, 0.01656322181224823, -0.001313482178375125, -0.019625281915068626, -0.05187742039561272, 0.03671330213546753, 0.0332404263317585, -0.05294264853000641, -0.015970755368471146, 0.01...
AnonymousSub/cline_squad2.0
[ "pytorch", "roberta", "question-answering", "transformers", "autotrain_compatible" ]
question-answering
{ "architectures": [ "RobertaForQuestionAnswering" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_re...
8
null
--- tags: - fastai --- # Amazing! 🥳 Congratulations on hosting your fastai model on the Hugging Face Hub! # Some next steps 1. Fill out this model card with more information (see the template below and the [documentation here](https://huggingface.co/docs/hub/model-repos))! 2. Create a demo in Gradio or Streamlit u...
[ -0.02170664444565773, -0.03312091529369354, 0.006928390357643366, 0.02291768603026867, 0.010587208904325962, 0.024608587846159935, -0.02954154461622238, -0.01672542467713356, -0.02882952056825161, 0.03267510235309601, 0.03176262602210045, 0.010438961908221245, 0.04351670667529106, 0.029931...
AnonymousSub/consert-emanuals-s10-SR
[ "pytorch", "bert", "text-classification", "transformers" ]
text-classification
{ "architectures": [ "BertForSequenceClassification" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_rep...
29
null
--- library_name: stable-baselines3 tags: - SpaceInvadersNoFrameskip-v4 - deep-reinforcement-learning - reinforcement-learning - stable-baselines3 model-index: - name: DQN results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: SpaceInvadersNoFrameskip-v4 ...
[ -0.040616437792778015, -0.015233812853693962, -0.016644610092043877, 0.03639013320207596, 0.04871446266770363, -0.004494138062000275, -0.014243341982364655, -0.02513893134891987, -0.03028259612619877, 0.05390831455588341, 0.021944936364889145, -0.031036462634801865, 0.018989378586411476, 0...
AnonymousSub/consert-s10-AR
[ "pytorch", "bert", "text-classification", "transformers" ]
text-classification
{ "architectures": [ "BertForSequenceClassification" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_rep...
31
null
--- license: cc-by-4.0 metrics: - bleu4 - meteor - rouge-l - bertscore - moverscore language: ko datasets: - lmqg/qg_koquad pipeline_tag: text2text-generation tags: - question answering widget: - text: "question: 매드 클라운이 참가해 큰 화제를 모았던 프로그램은?, context: 과거 소울 컴퍼니 소속으로 소울 컴퍼니 해체 후 현재의 소속사는 스타쉽 엑스이다. Mad Clown vs Crucial ...
[ 0.017133494839072227, -0.020531509071588516, -0.0017524416325613856, 0.024444304406642914, 0.03006364032626152, -0.00047384746721945703, -0.008523308672010899, 0.013321743346750736, -0.054693035781383514, 0.036968957632780075, 0.025177888572216034, 0.0005690544494427741, 0.02078486792743206,...
AnonymousSub/consert-techqa
[ "pytorch", "bert", "question-answering", "transformers", "autotrain_compatible" ]
question-answering
{ "architectures": [ "BertForQuestionAnswering" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_n...
4
2023-03-20T11:52:23Z
--- language: - en pipeline_tag: text-classification tags: - Economics --- # Pretrained model used for the NASDAQ_news dataset Model for Binary classification on headlines from the NASDAQ_news dataset. Label_0 = Downward movement Label_1 = Upward movement The target_variable is the return 20-minutes after an article ...
[ -0.015132335014641285, -0.01112672034651041, 0.014187285676598549, 0.04010442644357681, 0.0626809224486351, 0.021422669291496277, 0.005845225416123867, -0.018316272646188736, -0.024332785978913307, 0.04917621612548828, 0.016573891043663025, 0.008043729700148106, 0.008587789721786976, 0.029...
AnonymousSub/declutr-emanuals-s10-AR
[ "pytorch", "roberta", "text-classification", "transformers" ]
text-classification
{ "architectures": [ "RobertaForSequenceClassification" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "...
29
null
--- tags: - unity-ml-agents - ml-agents - deep-reinforcement-learning - reinforcement-learning - ML-Agents-SoccerTwos library_name: ml-agents --- # **poca** Agent playing **SoccerTwos** This is a trained model of a **poca** agent playing **SoccerTwos** using the [Unit...
[ -0.0208548903465271, -0.005533355288207531, 0.009700038470327854, 0.039517056196928024, 0.032394591718912125, 0.015976985916495323, -0.02813870646059513, -0.015584535896778107, -0.0172923244535923, 0.06239733099937439, 0.0068973759189248085, -0.00037729088217020035, 0.0105037996545434, 0.0...
AnonymousSub/declutr-emanuals-s10-SR
[ "pytorch", "roberta", "text-classification", "transformers" ]
text-classification
{ "architectures": [ "RobertaForSequenceClassification" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "...
28
2023-03-20T11:56:53Z
--- library_name: ml-agents tags: - SnowballTarget - deep-reinforcement-learning - reinforcement-learning - ML-Agents-SnowballTarget --- # **ppo** Agent playing **SnowballTarget** This is a trained model of a **ppo** agent playing **SnowballTarget** using the [Unity ML-Agents Library](https://github.com/Unity-Tech...
[ -0.028608018532395363, -0.004405091051012278, -0.017820825800299644, 0.05125970020890236, 0.036039356142282486, 0.026587164029479027, -0.0005911645712330937, -0.03376314043998718, -0.026063190773129463, 0.04731034114956856, 0.02642008103430271, -0.009139147587120533, 0.018975507467985153, ...
AnonymousSub/declutr-emanuals-techqa
[ "pytorch", "roberta", "question-answering", "transformers", "autotrain_compatible" ]
question-answering
{ "architectures": [ "RobertaForQuestionAnswering" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_re...
4
2023-03-20T11:57:33Z
--- tags: - unity-ml-agents - ml-agents - deep-reinforcement-learning - reinforcement-learning - ML-Agents-SoccerTwos library_name: ml-agents --- # **poca** Agent playing **SoccerTwos** This is a trained model of a **poca** agent playing **SoccerTwos** using the [Unit...
[ -0.02155161462724209, -0.005132281221449375, 0.010527059435844421, 0.03937961161136627, 0.03200216963887215, 0.015084865503013134, -0.028869401663541794, -0.015597638674080372, -0.015603665262460709, 0.060970306396484375, 0.006904967129230499, 0.00018832726345863193, 0.010375645011663437, ...
AnonymousSub/declutr-model-emanuals
[ "pytorch", "roberta", "fill-mask", "transformers", "autotrain_compatible" ]
fill-mask
{ "architectures": [ "RobertaForMaskedLM" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngra...
4
2023-03-20T11:58:00Z
--- library_name: stable-baselines3 tags: - SpaceInvadersNoFrameskip-v4 - deep-reinforcement-learning - reinforcement-learning - stable-baselines3 model-index: - name: DQN results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: SpaceInvadersNoFrameskip-v4 ...
[ -0.0394868366420269, -0.015343652106821537, -0.015110294334590435, 0.0357925146818161, 0.04821760579943657, -0.00617204187437892, -0.011594329960644245, -0.025180496275424957, -0.031910549849271774, 0.054261334240436554, 0.02469373308122158, -0.03225505352020264, 0.0171390138566494, 0.0156...
AnonymousSub/hier_triplet_epochs_1_shard_10
[ "pytorch", "bert", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "BertModel" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": nul...
8
null
--- license: creativeml-openrail-m language: - en --- V1:CloverMix is checkpoint merge model of ChillOutMix, LOFI, DDosMix and DreamShaper. V2:CloverMix is checkpoint merge model of ChillOutMix, LOFI, DDosMix ,DreamShaper and RetMix.
[ -0.020665161311626434, 0.004598795901983976, 0.003249908098950982, -0.010201112367212772, 0.048045564442873, 0.019888604059815407, 0.007489366456866264, 0.0038931970484554768, -0.008880767971277237, 0.07971428334712982, 0.041548751294612885, 0.004073451738804579, 0.0011379991192370653, 0.0...
AnonymousSub/roberta-base_squad2.0
[ "pytorch", "roberta", "question-answering", "transformers", "autotrain_compatible" ]
question-answering
{ "architectures": [ "RobertaForQuestionAnswering" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_re...
6
null
--- tags: - Pixelcopter-PLE-v0 - reinforce - reinforcement-learning - custom-implementation - deep-rl-class model-index: - name: Reinforce_PixelCopter_v2 results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: Pixelcopter-PLE-v0 type: Pixelcopter-PLE-v0 ...
[ -0.04040054604411125, 0.015316448174417019, 0.013642005622386932, 0.01848304271697998, 0.049176327884197235, -0.013825730420649052, -0.02037908509373665, -0.024105602875351906, -0.016373001039028168, 0.06783626973628998, 0.03655622899532318, -0.006422627251595259, 0.009790823794901371, -0....
AnonymousSub/rule_based_bert_hier_diff_equal_wts_epochs_1_shard_10
[ "pytorch", "bert", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "BertModel" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": nul...
6
null
--- license: apache-2.0 tags: - generated_from_trainer model-index: - name: labor_space_distilbert 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. --> # labor_space_...
[ -0.008626431226730347, 0.0004841555200982839, -0.038624007254838943, 0.029717447236180305, 0.06163564324378967, 0.02635885775089264, -0.02436254732310772, -0.01736571453511715, -0.04864702373743057, 0.06731850653886795, 0.04021661728620529, -0.009855184704065323, 0.016395287588238716, 0.03...
AnonymousSub/rule_based_bert_mean_diff_epochs_1_shard_10
[ "pytorch", "bert", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "BertModel" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": nul...
4
null
--- library_name: ml-agents tags: - Pyramids - deep-reinforcement-learning - reinforcement-learning - ML-Agents-Pyramids --- # **ppo** Agent playing **Pyramids** This is a trained model of a **ppo** agent playing **Pyramids** using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents). ...
[ -0.05123692750930786, 0.0025024262722581625, -0.005273669492453337, 0.05062755569815636, 0.025244107469916344, 0.03195345401763916, -0.008885080926120281, -0.023612966760993004, -0.002078861463814974, 0.05063037946820259, 0.02235802449285984, -0.014143646694719791, 0.007316843140870333, 0....
AnonymousSub/rule_based_bert_quadruplet_epochs_1_shard_1
[ "pytorch", "bert", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "BertModel" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": nul...
8
null
--- license: apache-2.0 tags: - generated_from_trainer datasets: - emotion metrics: - accuracy - f1 model-index: - name: distilbert-base-uncased-finetuned-emotion results: - task: name: Text Classification type: text-classification dataset: name: emotion type: emotion config: split...
[ -0.010152068920433521, 0.010383167304098606, -0.027792949229478836, 0.036100100725889206, 0.061194270849227905, 0.03243701905012131, -0.022014783695340157, -0.03587324917316437, -0.03309745341539383, 0.057223327457904816, 0.018157076090574265, -0.045765142887830734, 0.03478166460990906, 0....
AnonymousSub/rule_based_bert_triplet_epochs_1_shard_10
[ "pytorch", "bert", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "BertModel" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": nul...
4
null
--- license: apache-2.0 tags: - generated_from_keras_callback model-index: - name: rajakashh/final_huggingfacexx 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. --> # raja...
[ -0.03893028944730759, -0.004707792773842812, -0.0010310030775144696, 0.02386256493628025, 0.023686882108449936, 0.009816260077059269, -0.022712966427206993, -0.026544885709881783, -0.02841881476342678, 0.05844699963927269, 0.007249575573951006, -0.03245323896408081, 0.03330281004309654, 0....
AnonymousSub/rule_based_hier_quadruplet_0.1_epochs_1_shard_1
[ "pytorch", "bert", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "BertModel" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": nul...
4
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...
[ -0.01752704568207264, -0.018237341195344925, -0.006663015577942133, 0.03075355291366577, 0.051605574786663055, -0.017213912680745125, -0.010990951210260391, -0.00947714876383543, -0.05796391889452934, 0.053820088505744934, -0.0019773857202380896, -0.009838053025305271, 0.02559628151357174, ...
AnonymousSub/rule_based_hier_quadruplet_0.1_epochs_1_shard_1_squad2.0
[ "pytorch", "bert", "question-answering", "transformers", "autotrain_compatible" ]
question-answering
{ "architectures": [ "BertForQuestionAnswering" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_n...
4
null
--- tags: - autotrain - summarization language: - zh widget: - text: "I love AutoTrain 🤗" datasets: - lambdarw/autotrain-data-t5-pegasus_ch_ansmrc co2_eq_emissions: emissions: 4.429613533710655 --- # Model Trained Using AutoTrain - Problem type: Summarization - Model ID: 42285108445 - CO2 Emissions (in grams): 4.4...
[ -0.032630983740091324, -0.01784876175224781, 0.0007436653249897063, 0.03073269873857498, 0.03524160757660866, 0.01071247924119234, -0.03602837771177292, -0.028967667371034622, -0.03867456689476967, 0.07928167283535004, 0.022809777408838272, 0.02184792049229145, 0.009190871380269527, 0.0314...
AnonymousSub/rule_based_hier_quadruplet_epochs_1_shard_1
[ "pytorch", "bert", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "BertModel" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": nul...
8
null
# `vocabtrimmer/xlm-roberta-base-trimmed-fr-10000-tweet-sentiment-fr` This model is a fine-tuned version of [/home/asahi/lm-vocab-trimmer/ckpts/xlm-roberta-base-trimmed-fr-10000](https://huggingface.co//home/asahi/lm-vocab-trimmer/ckpts/xlm-roberta-base-trimmed-fr-10000) on the [cardiffnlp/tweet_sentiment_multilingua...
[ -0.010075562633574009, -0.026258978992700577, -0.008705822750926018, 0.019861122593283653, 0.027912715449929237, 0.022112298756837845, -0.01595180295407772, -0.023512836545705795, -0.0531085729598999, 0.03711038455367088, 0.022403942421078682, -0.049038853496313095, -0.023101579397916794, ...
AnonymousSub/rule_based_hier_quadruplet_epochs_1_shard_1_squad2.0
[ "pytorch", "bert", "question-answering", "transformers", "autotrain_compatible" ]
question-answering
{ "architectures": [ "BertForQuestionAnswering" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_n...
3
null
--- library_name: ml-agents tags: - SnowballTarget - deep-reinforcement-learning - reinforcement-learning - ML-Agents-SnowballTarget --- # **ppo** Agent playing **SnowballTarget** This is a trained model of a **ppo** agent playing **SnowballTarget** using the [Unity ML-Agents Library](https://github.com/Unity-Tech...
[ -0.028963491320610046, -0.005485600791871548, -0.01814512349665165, 0.052481088787317276, 0.03610600158572197, 0.026769332587718964, -0.0015730634331703186, -0.03514911234378815, -0.02589239552617073, 0.046516381204128265, 0.026450276374816895, -0.007970739156007767, 0.017977746203541756, ...
AnonymousSub/rule_based_hier_triplet_epochs_1_shard_1_squad2.0
[ "pytorch", "bert", "question-answering", "transformers", "autotrain_compatible" ]
question-answering
{ "architectures": [ "BertForQuestionAnswering" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_n...
2
null
--- license: apache-2.0 tags: - generated_from_keras_callback model-index: - name: rajakashh/final_huggingfacez 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. --> # rajak...
[ -0.037912748754024506, -0.010209639556705952, -0.0024825839791446924, 0.024037284776568413, 0.022902153432369232, 0.014027297496795654, -0.0248220507055521, -0.022217577323317528, -0.028151970356702805, 0.05605350434780121, 0.012702850624918938, -0.03211267665028572, 0.028153827413916588, ...
AnonymousSub/rule_based_hier_triplet_epochs_1_shard_1_wikiqa_copy
[ "pytorch", "bert", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "BertModel" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": nul...
1
null
--- 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 ...
[ -0.03757685050368309, -0.0031216563656926155, -0.0056617530062794685, 0.02586422860622406, 0.04607674106955528, -0.020934946835041046, -0.00615603057667613, -0.02736011892557144, -0.032598551362752914, 0.06651858240365982, 0.031922511756420135, -0.023272477090358734, 0.023084625601768494, ...
AnonymousSub/rule_based_only_classfn_epochs_1_shard_1
[ "pytorch", "bert", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "BertModel" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": nul...
4
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 ...
[ -0.037488602101802826, -0.0027065216563642025, -0.004868022631853819, 0.02556844986975193, 0.04514992982149124, -0.0218869149684906, -0.005103082396090031, -0.02779349498450756, -0.03359325975179672, 0.06605944782495499, 0.03227240592241287, -0.023496057838201523, 0.022839009761810303, 0.0...
AnonymousSub/rule_based_only_classfn_epochs_1_shard_10
[ "pytorch", "bert", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "BertModel" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": nul...
7
null
--- language: - zh - en tags: - glm - chatglm - thudm --- # ChatGLM-6B **本仓库已经不再维护,请使用 [ChatGLM-6B-INT4](https://huggingface.co/THUDM/chatglm-6b-int4)** ## 介绍 ChatGLM-6B 是一个开源的、支持中英双语问答的对话语言模型,基于 [General Language Model (GLM)](https://github.com/THUDM/GLM) 架构,具有 62 亿参数。结合模型量化技术,用户可以在消费级的显卡上进行本地部署(INT4 量化级别下最低只需 6GB 显存...
[ -0.030626213178038597, -0.024389801546931267, -0.006036283448338509, 0.042747076600790024, 0.04069015756249428, 0.02170404978096485, -0.027028923854231834, -0.007836396805942059, -0.02845008485019207, 0.04614035412669182, 0.02835005708038807, -0.01654672995209694, -0.001119381980970502, 0....
AnonymousSub/rule_based_only_classfn_epochs_1_shard_1_wikiqa
[ "pytorch", "bert", "text-classification", "transformers" ]
text-classification
{ "architectures": [ "BertForSequenceClassification" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_rep...
32
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 ...
[ -0.03724020719528198, -0.0029844501987099648, -0.0051594325341284275, 0.025884553790092468, 0.04560810327529907, -0.021367376670241356, -0.005428540986031294, -0.027791112661361694, -0.03320476785302162, 0.0662359744310379, 0.032483167946338654, -0.023352090269327164, 0.023046456277370453, ...
AnonymousSub/rule_based_roberta_bert_quadruplet_epochs_1_shard_10
[ "pytorch", "roberta", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "RobertaModel" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
8
null
# `vocabtrimmer/xlm-roberta-base-trimmed-fr-15000-tweet-sentiment-fr` This model is a fine-tuned version of [/home/asahi/lm-vocab-trimmer/ckpts/xlm-roberta-base-trimmed-fr-15000](https://huggingface.co//home/asahi/lm-vocab-trimmer/ckpts/xlm-roberta-base-trimmed-fr-15000) on the [cardiffnlp/tweet_sentiment_multilingua...
[ -0.01121300645172596, -0.02672915905714035, -0.009232602082192898, 0.018717780709266663, 0.030134018510580063, 0.020437031984329224, -0.015181888826191425, -0.024006202816963196, -0.05323784053325653, 0.03720426186919212, 0.02263559401035309, -0.04896035045385361, -0.024033529683947563, 0....
AnonymousSub/rule_based_roberta_bert_quadruplet_epochs_1_shard_1_wikiqa
[ "pytorch", "roberta", "text-classification", "transformers" ]
text-classification
{ "architectures": [ "RobertaForSequenceClassification" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "...
23
2023-03-20T13:07:14Z
--- library_name: stable-baselines3 tags: - PandaReachDense-v2 - deep-reinforcement-learning - reinforcement-learning - stable-baselines3 model-index: - name: A2C results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: PandaReachDense-v2 type: PandaReach...
[ -0.05017634853720665, -0.016222093254327774, -0.008848514407873154, 0.03615919500589371, 0.04119943827390671, 0.0029856672044843435, -0.0214421134442091, -0.010425366461277008, -0.037718266248703, 0.05693665146827698, 0.024168256670236588, -0.0031193194445222616, 0.031598106026649475, 0.00...
AnonymousSub/rule_based_roberta_bert_triplet_epochs_1_shard_10
[ "pytorch", "roberta", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "RobertaModel" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
2
2023-03-20T13:09:41Z
Please refer to [flaim](https://github.com/bobmcdear/flaim) for sample usage and more information.
[ -0.028801413252949715, -0.0177990160882473, 0.009709034115076065, 0.040950655937194824, 0.04654869809746742, -0.0027751356828957796, 0.013433797284960747, -0.008017306216061115, -0.036281563341617584, 0.04279222711920738, 0.02568740025162697, -0.0006620007916353643, 0.03954673185944557, 0....
AnonymousSub/rule_based_roberta_bert_triplet_epochs_1_shard_1_squad2.0
[ "pytorch", "roberta", "question-answering", "transformers", "autotrain_compatible" ]
question-answering
{ "architectures": [ "RobertaForQuestionAnswering" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_re...
3
null
Please refer to [flaim](https://github.com/bobmcdear/flaim) for sample usage and more information.
[ -0.028801413252949715, -0.0177990160882473, 0.009709034115076065, 0.040950655937194824, 0.04654869809746742, -0.0027751356828957796, 0.013433797284960747, -0.008017306216061115, -0.036281563341617584, 0.04279222711920738, 0.02568740025162697, -0.0006620007916353643, 0.03954673185944557, 0....
AnonymousSub/rule_based_roberta_bert_triplet_epochs_1_shard_1_wikiqa
[ "pytorch", "roberta", "text-classification", "transformers" ]
text-classification
{ "architectures": [ "RobertaForSequenceClassification" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "...
28
null
--- license: openrail++ tags: - stable-diffusion - text-to-image pinned: true --- # Stable Diffusion v2-1-unclip Model Card This model card focuses on the model associated with the Stable Diffusion v2-1 model, codebase available [here](https://github.com/Stability-AI/stablediffusion). This `stable-diffusion-2-1-uncli...
[ -0.0008717486052773893, -0.011614770628511906, -0.012783247046172619, 0.03484710305929184, 0.05329402536153793, 0.0018399234395474195, 0.01489035040140152, -0.013488644734025002, -0.021467439830303192, 0.051832810044288635, 0.02200132980942726, -0.007670281454920769, 0.0036714680027216673, ...
AnonymousSub/rule_based_roberta_hier_quadruplet_0.1_epochs_1_shard_1
[ "pytorch", "roberta", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "RobertaModel" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
6
null
--- library_name: ml-agents tags: - SnowballTarget - deep-reinforcement-learning - reinforcement-learning - ML-Agents-SnowballTarget --- # **ppo** Agent playing **SnowballTarget** This is a trained model of a **ppo** agent playing **SnowballTarget** using the [Unity ML-Agents Library](https://github.com/Unity-Tech...
[ -0.025767089799046516, -0.0054122814908623695, -0.01812889613211155, 0.053642310202121735, 0.03732161223888397, 0.0233377143740654, -0.00041121928370557725, -0.035388898104429245, -0.02865668386220932, 0.04551316425204277, 0.02467901073396206, -0.009915830567479134, 0.013587243854999542, 0...
AnonymousSub/rule_based_roberta_hier_quadruplet_0.1_epochs_1_shard_1_squad2.0
[ "pytorch", "roberta", "question-answering", "transformers", "autotrain_compatible" ]
question-answering
{ "architectures": [ "RobertaForQuestionAnswering" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_re...
4
null
--- library_name: ml-agents tags: - Pyramids - deep-reinforcement-learning - reinforcement-learning - ML-Agents-Pyramids --- # **ppo** Agent playing **Pyramids** This is a trained model of a **ppo** agent playing **Pyramids** using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents). ...
[ -0.051768768578767776, 0.0009838606929406524, -0.005470725242048502, 0.051028672605752945, 0.025180837139487267, 0.03205724060535431, -0.010347103700041771, -0.022729365155100822, -0.0011849642032757401, 0.04983120039105415, 0.02365710213780403, -0.012846643105149269, 0.006394302472472191, ...
AnonymousSub/rule_based_roberta_hier_quadruplet_epochs_1_shard_1_squad2.0
[ "pytorch", "roberta", "question-answering", "transformers", "autotrain_compatible" ]
question-answering
{ "architectures": [ "RobertaForQuestionAnswering" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_re...
2
null
--- tags: - Taxi-v3 - q-learning - reinforcement-learning - custom-implementation model-index: - name: Taxi_v1 results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: Taxi-v3 type: Taxi-v3 metrics: - type: mean_reward value: 7.50 +/- 2.76 ...
[ -0.020961614325642586, -0.015344779938459396, -0.008796550333499908, 0.025910574942827225, 0.0468427948653698, -0.0014308750396594405, -0.01816735416650772, 0.007765186484903097, -0.036706551909446716, 0.05280574411153793, 0.018218381330370903, -0.006786481011658907, 0.012349529191851616, ...
AnonymousSub/rule_based_roberta_hier_triplet_0.1_epochs_1_shard_1
[ "pytorch", "roberta", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "RobertaModel" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
6
null
--- license: cc-by-4.0 metrics: - bleu4 - meteor - rouge-l - bertscore - moverscore language: it datasets: - lmqg/qg_itquad pipeline_tag: text2text-generation tags: - question answering widget: - text: "question: Quale batterio ha il nome del paese che colpisce di più nel suo nome?, context: Il complesso M. tubercolos...
[ 0.010812762193381786, -0.01152182649821043, 0.0039857360534369946, 0.02483181282877922, 0.05932186543941498, 0.0029171840287745, -0.0024073468521237373, -0.008121541701257229, -0.04681900888681412, 0.026452360674738884, 0.018175413832068443, -0.000992975546978414, -0.017108645290136337, 0....
AnonymousSub/rule_based_roberta_hier_triplet_epochs_1_shard_1
[ "pytorch", "roberta", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "RobertaModel" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
4
null
--- license: apache-2.0 tags: - generated_from_trainer model-index: - name: bsc-bio-ehr-es-finetuned-clinais 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. --> # bs...
[ -0.020253125578165054, -0.014989935792982578, -0.00682090362533927, 0.016699254512786865, 0.03327175974845886, 0.0036052747163921595, -0.0057206423953175545, 0.007032726891338825, -0.03178936988115311, 0.04177486523985863, 0.0071475571021437645, -0.026839729398489, 0.013034866191446781, 0....
AnonymousSub/rule_based_roberta_hier_triplet_epochs_1_shard_10
[ "pytorch", "roberta", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "RobertaModel" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
6
2023-03-20T13:31:47Z
--- language: - en pipeline_tag: text-classification tags: - Economics --- # Pretrained model used for the NASDAQ_news dataset Model for Binary classification on headlines from the NASDAQ_news dataset. Label_0 = Downward movement Label_1 = Upward movement The target_variable is the return 10-minutes after an article ...
[ -0.015134799294173717, -0.011172632686793804, 0.01573113724589348, 0.04022230952978134, 0.0636214092373848, 0.021540960296988487, 0.004370033275336027, -0.01829577051103115, -0.024731794372200966, 0.04919661581516266, 0.016690777614712715, 0.008681275881826878, 0.009807154536247253, 0.0300...
AnonymousSub/rule_based_roberta_only_classfn_epochs_1_shard_10
[ "pytorch", "roberta", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "RobertaModel" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
5
null
--- tags: - Pixelcopter-PLE-v0 - reinforce - reinforcement-learning - custom-implementation - deep-rl-class model-index: - name: unit422 results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: Pixelcopter-PLE-v0 type: Pixelcopter-PLE-v0 metrics: ...
[ -0.04309465363621712, 0.015531477518379688, 0.014339008368551731, 0.02119540423154831, 0.04916257783770561, -0.0125078484416008, -0.020258504897356033, -0.02930292673408985, -0.019707616418600082, 0.06545808166265488, 0.03588377684354782, -0.008439562283456326, 0.008356603793799877, -0.008...
AnonymousSub/rule_based_roberta_only_classfn_twostage_epochs_1_shard_1
[ "pytorch", "roberta", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "RobertaModel" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
10
2023-03-20T13:41:48Z
--- license: apache-2.0 tags: - generated_from_trainer metrics: - rouge - bleu model-index: - name: t5-end2end-question-generation 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 t...
[ -0.004828716162592173, -0.006466258317232132, -0.005064170341938734, 0.03158895671367645, 0.0378214567899704, -0.0025055892765522003, -0.0271182581782341, -0.01567424088716507, -0.043663736432790756, 0.04125208035111427, 0.01230550091713667, -0.03335430845618248, 0.0039871735498309135, 0.0...
AnonymousSub/rule_based_roberta_only_classfn_twostage_epochs_1_shard_10
[ "pytorch", "roberta", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "RobertaModel" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
2
null
--- license: cc-by-4.0 metrics: - bleu4 - meteor - rouge-l - bertscore - moverscore language: ko datasets: - lmqg/qg_koquad pipeline_tag: text2text-generation tags: - question answering widget: - text: "question: 매드 클라운이 참가해 큰 화제를 모았던 프로그램은?, context: 과거 소울 컴퍼니 소속으로 소울 컴퍼니 해체 후 현재의 소속사는 스타쉽 엑스이다. Mad Clown vs Crucial ...
[ 0.017133494839072227, -0.020531509071588516, -0.0017524416325613856, 0.024444304406642914, 0.03006364032626152, -0.00047384746721945703, -0.008523308672010899, 0.013321743346750736, -0.054693035781383514, 0.036968957632780075, 0.025177888572216034, 0.0005690544494427741, 0.02078486792743206,...
AnonymousSub/rule_based_roberta_only_classfn_twostage_epochs_1_shard_1_wikiqa
[ "pytorch", "roberta", "text-classification", "transformers" ]
text-classification
{ "architectures": [ "RobertaForSequenceClassification" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "...
24
2023-03-20T13:50:30Z
--- tags: - Pixelcopter-PLE-v0 - reinforce - reinforcement-learning - custom-implementation - deep-rl-class model-index: - name: Pixelcopter-PLE-v0 results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: Pixelcopter-PLE-v0 type: Pixelcopter-PLE-v0 me...
[ -0.04106178134679794, 0.013906602747738361, 0.014869722537696362, 0.019906464964151382, 0.049056943506002426, -0.013366497121751308, -0.019443411380052567, -0.028309542685747147, -0.017093000933527946, 0.06512068212032318, 0.03587619960308075, -0.007907751016318798, 0.008015627041459084, -...
AnonymousSub/rule_based_roberta_twostage_quadruplet_epochs_1_shard_1
[ "pytorch", "roberta", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "RobertaModel" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
5
null
--- 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 ...
[ -0.03724048286676407, -0.0031514072325080633, -0.005461303982883692, 0.02570754662156105, 0.045494213700294495, -0.021173959597945213, -0.005724985618144274, -0.02758917026221752, -0.033447131514549255, 0.06680283695459366, 0.03192109614610672, -0.023727834224700928, 0.02237788587808609, 0...
AnonymousSub/rule_based_roberta_twostagequadruplet_hier_epochs_1_shard_10
[ "pytorch", "roberta", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "RobertaModel" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
2
null
# `vocabtrimmer/xlm-roberta-base-trimmed-fr-60000-tweet-sentiment-fr` This model is a fine-tuned version of [/home/asahi/lm-vocab-trimmer/ckpts/xlm-roberta-base-trimmed-fr-60000](https://huggingface.co//home/asahi/lm-vocab-trimmer/ckpts/xlm-roberta-base-trimmed-fr-60000) on the [cardiffnlp/tweet_sentiment_multilingua...
[ -0.010718072764575481, -0.02682429924607277, -0.009850475005805492, 0.02022506855428219, 0.02830803021788597, 0.020863287150859833, -0.01644480787217617, -0.023077048361301422, -0.052838198840618134, 0.037745311856269836, 0.02279532514512539, -0.050025057047605515, -0.02314717322587967, 0....
AnonymousSub/rule_based_twostagetriplet_epochs_1_shard_1
[ "pytorch", "bert", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "BertModel" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": nul...
10
null
--- library_name: ml-agents tags: - Pyramids - deep-reinforcement-learning - reinforcement-learning - ML-Agents-Pyramids --- # **ppo** Agent playing **Pyramids** This is a trained model of a **ppo** agent playing **Pyramids** using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents). ...
[ -0.05146840587258339, 0.002615393837913871, -0.0060137789696455, 0.05031672120094299, 0.02490059845149517, 0.03100493736565113, -0.0109881442040205, -0.02323117107152939, -0.002270421711727977, 0.050400473177433014, 0.02432267740368843, -0.014509514905512333, 0.007838945835828781, 0.023874...
ArBert/albert-base-v2-finetuned-ner-gmm
[ "pytorch", "tensorboard", "albert", "token-classification", "transformers", "autotrain_compatible" ]
token-classification
{ "architectures": [ "AlbertForTokenClassification" ], "model_type": "albert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_re...
8
2023-03-20T15:00:05Z
--- 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 ...
[ -0.037633247673511505, -0.0021913964301347733, -0.005098503082990646, 0.025533219799399376, 0.04560663551092148, -0.02150784432888031, -0.005306311417371035, -0.02749459259212017, -0.03243321180343628, 0.06659098714590073, 0.03190087899565697, -0.023297946900129318, 0.023023825138807297, 0...
ArBert/albert-base-v2-finetuned-ner-kmeans
[ "pytorch", "tensorboard", "albert", "token-classification", "transformers", "autotrain_compatible" ]
token-classification
{ "architectures": [ "AlbertForTokenClassification" ], "model_type": "albert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_re...
8
2023-03-20T15:05:48Z
--- license: creativeml-openrail-m tags: - text-to-image --- ### arki-20230319-15-analog-cnst-4000-steps on Stable Diffusion via Dreambooth #### model by NickKolok This your the Stable Diffusion model fine-tuned the arki-20230319-15-analog-cnst-4000-steps concept taught to Stable Diffusion with Dreambooth. #I...
[ -0.0446888767182827, -0.011413359083235264, -0.027005081996321678, 0.014260519295930862, 0.029310883954167366, 0.01019611582159996, 0.0014199498109519482, -0.0028973082080483437, -0.02997116930782795, 0.04528924077749252, 0.027073562145233154, 0.011087060905992985, -0.01512729562819004, 0....
AriakimTaiyo/DialoGPT-small-Kumiko
[ "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...
11
null
--- license: mit datasets: - squad_v2 language: - en tags: - Bert - SQuAD2.0 - SQuAD pipeline_tag: question-answering --- # Extract QA Model (SQuAD2.0) ## Model Information Pretrained model: google/bert_uncased_L-12_H-768_A-12 ## Training Hyperparameters ```Python epochs = 2 batch_size = 24 learning_rate = 3e-5 ma...
[ 0.009426779113709927, -0.03188473731279373, -0.03460302948951721, 0.059640467166900635, 0.04116889089345932, -0.004377410747110844, -0.024226011708378792, 0.021279258653521538, -0.048430878669023514, 0.0367756262421608, 0.01907443441450596, 0.0019903327338397503, 0.009802151471376419, 0.05...
Augustvember/wokka
[ "gpt2", "text-generation", "transformers" ]
text-generation
{ "architectures": [ "GPT2LMHeadModel" ], "model_type": "gpt2", "task_specific_params": { "conversational": { "max_length": 1000 }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
4
null
cherrylinemix: https://civitai.com/models/12980/cherrylinemix
[ -0.019880905747413635, 0.003619320224970579, 0.0021922714076936245, 0.02762705087661743, 0.05714039504528046, -0.0040221912786364555, 0.00165952043607831, 0.0029933645855635405, -0.028044164180755615, 0.05285469815135002, 0.07971487939357758, -0.0011674927081912756, 0.013883818872272968, 0...
Awsaf/large-eren
[ "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: - feature-extraction library_name: fasttext language: ja widget: - text: apple example_title: apple --- # fastText (Japanese) fastText is an open-source, free, lightweight library that allows users to learn text representations and text classifiers. It works on standard, generic hardwa...
[ -0.0007079906645230949, -0.0364331416785717, -0.030706999823451042, 0.06259209662675858, 0.01601005718111992, 0.044918663799762726, -0.005199619568884373, -0.01950303465127945, -0.0208458062261343, 0.042486757040023804, 0.023145319893956184, 0.020491989329457283, 0.015440335497260094, 0.03...
Axon/resnet18-v1
[ "dataset:ImageNet", "arxiv:1512.03385", "Axon", "Elixir", "license:apache-2.0" ]
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: - feature-extraction library_name: fasttext language: jv widget: - text: apple example_title: apple --- # fastText (Javanese) fastText is an open-source, free, lightweight library that allows users to learn text representations and text classifiers. It works on standard, generic hardwa...
[ -0.0016448848182335496, -0.03503314033150673, -0.03079976513981819, 0.06121290102601051, 0.016461342573165894, 0.04493338614702225, -0.006252131890505552, -0.019028209149837494, -0.020702432841062546, 0.0415252149105072, 0.023033427074551582, 0.021762359887361526, 0.014991344884037971, 0.0...
Axon/resnet34-v1
[ "dataset:ImageNet", "arxiv:1512.03385", "Axon", "Elixir", "license:apache-2.0" ]
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: - Pixelcopter-PLE-v0 - reinforce - reinforcement-learning - custom-implementation - deep-rl-class model-index: - name: Pixelcopter-PLE-v0 results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: Pixelcopter-PLE-v0 type: Pixelcopter-PLE-v0 me...
[ -0.04125150665640831, 0.013848189264535904, 0.013779825530946255, 0.02059928886592388, 0.0491102859377861, -0.012457986362278461, -0.019999293610453606, -0.028328074142336845, -0.01688474602997303, 0.06485195457935333, 0.036162253469228745, -0.007723025977611542, 0.008205221965909004, -0.0...
Ayham/albert_distilgpt2_summarization_cnn_dailymail
[ "pytorch", "tensorboard", "encoder-decoder", "text2text-generation", "dataset:cnn_dailymail", "transformers", "generated_from_trainer", "autotrain_compatible" ]
text2text-generation
{ "architectures": [ "EncoderDecoderModel" ], "model_type": "encoder-decoder", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_re...
9
null
--- license: apache-2.0 tags: - generated_from_keras_callback model-index: - name: ishanjain/my_awesome_qa_model 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. --> # isha...
[ -0.03269096091389656, -0.021357020363211632, -0.005065239034593105, 0.01894775591790676, 0.0321909636259079, 0.0013891203561797738, -0.004181169904768467, -0.01282170508056879, -0.030113300308585167, 0.05857139825820923, 0.012273779138922691, -0.013389941304922104, 0.011900553479790688, 0....
Ayham/albert_gpt2_Full_summarization_cnndm
[ "pytorch", "tensorboard", "encoder-decoder", "text2text-generation", "dataset:cnn_dailymail", "transformers", "generated_from_trainer", "autotrain_compatible" ]
text2text-generation
{ "architectures": [ "EncoderDecoderModel" ], "model_type": "encoder-decoder", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_re...
9
null
--- license: mit tags: - feature-extraction library_name: fasttext language: ky widget: - text: apple example_title: apple --- # fastText (Kirghiz) fastText is an open-source, free, lightweight library that allows users to learn text representations and text classifiers. It works on standard, generic hardwar...
[ -0.0007236608653329313, -0.03481994941830635, -0.031291622668504715, 0.058763302862644196, 0.016598859801888466, 0.04489314556121826, -0.010156134143471718, -0.016918480396270752, -0.023249508813023567, 0.04476924613118172, 0.024726396426558495, 0.021708717569708824, 0.01022238191217184, 0...
Ayham/albert_gpt2_summarization_cnndm
[ "pytorch", "tensorboard", "encoder-decoder", "text2text-generation", "dataset:cnn_dailymail", "transformers", "generated_from_trainer", "autotrain_compatible" ]
text2text-generation
{ "architectures": [ "EncoderDecoderModel" ], "model_type": "encoder-decoder", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_re...
6
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...
[ -0.017557188868522644, -0.017750591039657593, -0.007206341717392206, 0.030507085844874382, 0.05258547142148018, -0.017303047701716423, -0.011623342521488667, -0.008534694090485573, -0.05922585353255272, 0.05422601103782654, -0.002306667622178793, -0.009853634051978588, 0.025256359949707985, ...
Ayham/albert_gpt2_summarization_xsum
[ "pytorch", "tensorboard", "encoder-decoder", "text2text-generation", "dataset:xsum", "transformers", "generated_from_trainer", "autotrain_compatible" ]
text2text-generation
{ "architectures": [ "EncoderDecoderModel" ], "model_type": "encoder-decoder", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_re...
7
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: 7.52 +/- 2.77...
[ -0.019410470500588417, -0.01620647683739662, -0.008149073459208012, 0.026542412117123604, 0.049198269844055176, -0.0015161397168412805, -0.019184144213795662, 0.007342007011175156, -0.03742973133921623, 0.05234745889902115, 0.016824817284941673, -0.007926074787974358, 0.012255744077265263, ...
Ayham/roberta_distilgpt2_summarization_cnn_dailymail
[ "pytorch", "tensorboard", "encoder-decoder", "text2text-generation", "dataset:cnn_dailymail", "transformers", "generated_from_trainer", "autotrain_compatible" ]
text2text-generation
{ "architectures": [ "EncoderDecoderModel" ], "model_type": "encoder-decoder", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_re...
4
2023-03-20T19:09:44Z
--- tags: - CartPole-v1 - deep-reinforcement-learning - reinforcement-learning - custom-implementation library_name: cleanrl model-index: - name: DQPN_freq results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: CartPole-v1 type: CartPole-v1 metrics:...
[ -0.015906117856502533, 0.0007634093635715544, -0.004609618801623583, 0.03637038916349411, 0.029458537697792053, -0.024435173720121384, -0.008049308322370052, -0.01679982990026474, -0.028267573565244675, 0.06135861575603485, -0.006276227999478579, -0.010957625694572926, -0.011488947086036205,...
Ayham/robertagpt2_xsum4
[ "pytorch", "tensorboard", "encoder-decoder", "text2text-generation", "transformers", "generated_from_trainer", "autotrain_compatible" ]
text2text-generation
{ "architectures": [ "EncoderDecoderModel" ], "model_type": "encoder-decoder", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_re...
8
2023-03-20T19:20:53Z
--- license: mit tags: - feature-extraction library_name: fasttext language: lt widget: - text: apple example_title: apple --- # fastText (Lithuanian) fastText is an open-source, free, lightweight library that allows users to learn text representations and text classifiers. It works on standard, generic hard...
[ 0.0014542711433023214, -0.032017629593610764, -0.03310764953494072, 0.059583477675914764, 0.022555556148290634, 0.043645646423101425, -0.009043144062161446, -0.01768733561038971, -0.025792555883526802, 0.042046938091516495, 0.025637876242399216, 0.019809475168585777, 0.010084648616611958, ...
Ayham/xlnet_gpt2_summarization_xsum
[ "pytorch", "tensorboard", "encoder-decoder", "text2text-generation", "dataset:xsum", "transformers", "generated_from_trainer", "autotrain_compatible" ]
text2text-generation
{ "architectures": [ "EncoderDecoderModel" ], "model_type": "encoder-decoder", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_re...
13
2023-03-20T19:28:09Z
--- library_name: ml-agents tags: - SnowballTarget - deep-reinforcement-learning - reinforcement-learning - ML-Agents-SnowballTarget --- # **ppo** Agent playing **SnowballTarget** This is a trained model of a **ppo** agent playing **SnowballTarget** using the [Unity ML-Agents Library](https://github.com/Unity-Tech...
[ -0.030705174431204796, -0.0060500092804431915, -0.01610502414405346, 0.05159147083759308, 0.03673878684639931, 0.026466118171811104, 0.0009494155528955162, -0.033893559128046036, -0.025445982813835144, 0.04769403859972954, 0.02729121595621109, -0.008367031812667847, 0.020259374752640724, 0...
Ayou/chinese_mobile_bert
[ "pytorch", "mobilebert", "fill-mask", "transformers", "license:apache-2.0", "autotrain_compatible" ]
fill-mask
{ "architectures": [ "MobileBertForMaskedLM" ], "model_type": "mobilebert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repea...
16
null
--- tags: - unity-ml-agents - ml-agents - deep-reinforcement-learning - reinforcement-learning - ML-Agents-Huggy library_name: ml-agents --- # **ppo** Agent playing **Huggy** This is a trained model of a **ppo** agent playing **Huggy** using the [Unity ML-Agents Libra...
[ -0.04110943153500557, -0.001966407522559166, -0.00790563877671957, 0.04905811697244644, 0.028567738831043243, 0.022231843322515488, -0.025328440591692924, -0.037173934280872345, -0.0062917242757976055, 0.049179792404174805, 0.02124984748661518, -0.009599904529750347, 0.019144844263792038, ...
Ayran/DialoGPT-medium-harry-potter-1-through-4-plus-6
[ "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...
12
null
--- license: apache-2.0 tags: - generated_from_trainer datasets: - squad model-index: - name: my_awesome_qa_model 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. --> ...
[ -0.017218830063939095, -0.01710723713040352, -0.0049741799011826515, 0.04324210062623024, 0.043334364891052246, 0.0016900964546948671, -0.015154731459915638, 0.007545072119683027, -0.030463675037026405, 0.04777757450938225, 0.0077315326780080795, -0.009497418999671936, -0.0015971793327480555...
Ayran/DialoGPT-small-gandalf
[ "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...
11
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 ...
[ -0.03755960613489151, -0.0026990468613803387, -0.005252393893897533, 0.025306077674031258, 0.04509758576750755, -0.021497363224625587, -0.005611221771687269, -0.028210807591676712, -0.03330599516630173, 0.06650044023990631, 0.03239090368151665, -0.023257210850715637, 0.02209893986582756, 0...
Ayran/DialoGPT-small-harry-potter-1-through-3
[ "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...
12
null
--- tags: - CartPole-v1 - deep-reinforcement-learning - reinforcement-learning - custom-implementation library_name: cleanrl model-index: - name: DQN results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: CartPole-v1 type: CartPole-v1 metrics: -...
[ -0.017839422449469566, -0.0002551478974055499, 0.0011445300187915564, 0.0323810912668705, 0.03085980750620365, -0.024878691881895065, -0.015650086104869843, -0.01864374242722988, -0.028939388692378998, 0.061855632811784744, -0.009228833019733429, -0.00503587769344449, -0.004549561534076929, ...
Ayu/Shiriro
[]
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 - deep-reinforcement-learning - reinforcement-learning - custom-implementation library_name: cleanrl model-index: - name: DQPN_freq results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: CartPole-v1 type: CartPole-v1 metrics:...
[ -0.015183060429990292, 0.00037160085048526525, -0.0036313068121671677, 0.03678165003657341, 0.02883286029100418, -0.02437525987625122, -0.008969026617705822, -0.01608928292989731, -0.02803940698504448, 0.06175743415951729, -0.006945961620658636, -0.010094116441905499, -0.012396100908517838, ...
AyushPJ/ai-club-inductions-21-nlp-ALBERT
[ "pytorch", "albert", "question-answering", "transformers", "generated_from_trainer", "autotrain_compatible" ]
question-answering
{ "architectures": [ "AlbertForQuestionAnswering" ], "model_type": "albert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repe...
8
null
--- tags: - CartPole-v1 - deep-reinforcement-learning - reinforcement-learning - custom-implementation library_name: cleanrl model-index: - name: DQN results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: CartPole-v1 type: CartPole-v1 metrics: -...
[ -0.01750427670776844, -0.00024134064733516425, 0.00019078671175520867, 0.032468393445014954, 0.031279049813747406, -0.02493911050260067, -0.016019772738218307, -0.018514033406972885, -0.02887633815407753, 0.061240822076797485, -0.008333779871463776, -0.005581575911492109, -0.0044977064244449...
AyushPJ/ai-club-inductions-21-nlp-XLNet
[ "pytorch", "xlnet", "question-answering", "transformers", "generated_from_trainer", "autotrain_compatible" ]
question-answering
{ "architectures": [ "XLNetForQuestionAnsweringSimple" ], "model_type": "xlnet", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_...
9
null
--- tags: - CartPole-v1 - deep-reinforcement-learning - reinforcement-learning - custom-implementation library_name: cleanrl model-index: - name: DQPN_freq results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: CartPole-v1 type: CartPole-v1 metrics:...
[ -0.017087996006011963, 0.0004242025315761566, -0.003509311703965068, 0.03738255426287651, 0.02902681939303875, -0.023282699286937714, -0.008403518237173557, -0.017015652731060982, -0.028354350477457047, 0.06043776124715805, -0.004789010155946016, -0.010169354267418385, -0.010806011967360973,...
AyushPJ/ai-club-inductions-21-nlp-roBERTa-base-squad-v2
[ "pytorch", "roberta", "question-answering", "transformers", "generated_from_trainer", "autotrain_compatible" ]
question-answering
{ "architectures": [ "RobertaForQuestionAnswering" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_re...
8
null
--- tags: - CartPole-v1 - deep-reinforcement-learning - reinforcement-learning - custom-implementation library_name: cleanrl model-index: - name: DQN results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: CartPole-v1 type: CartPole-v1 metrics: -...
[ -0.017434339970350266, 0.0001807767985155806, 0.0006428763153962791, 0.03225314989686012, 0.03186960518360138, -0.024981779977679253, -0.015632886439561844, -0.018957706168293953, -0.02946445904672146, 0.06196100264787674, -0.007835155352950096, -0.0045854696072638035, -0.005547882989048958,...
AyushPJ/test-squad-trained-finetuned-squad
[ "pytorch", "tensorboard", "distilbert", "question-answering", "dataset:squad", "transformers", "generated_from_trainer", "autotrain_compatible" ]
question-answering
{ "architectures": [ "DistilBertForQuestionAnswering" ], "model_type": "distilbert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, ...
8
2023-03-20T19:41:56Z
--- tags: - CartPole-v1 - deep-reinforcement-learning - reinforcement-learning - custom-implementation library_name: cleanrl model-index: - name: DQPN_freq results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: CartPole-v1 type: CartPole-v1 metrics:...
[ -0.016097774729132652, 0.00035500957164913416, -0.002666862914338708, 0.03693067654967308, 0.028380012139678, -0.023345990106463432, -0.009177664294838905, -0.01668061688542366, -0.02841951511800289, 0.06142623722553253, -0.005761334206908941, -0.009529205039143562, -0.011926323175430298, ...
Azaghast/DistilBART-SCP-ParaSummarization
[ "pytorch", "bart", "text2text-generation", "transformers", "autotrain_compatible" ]
text2text-generation
{ "architectures": [ "BartForConditionalGeneration" ], "model_type": "bart", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": true, "length_penalty": 2, "max_length": 142, "min_length": 56, "no_repeat_ngr...
8
null
--- tags: - CartPole-v1 - deep-reinforcement-learning - reinforcement-learning - custom-implementation library_name: cleanrl model-index: - name: DQPN_freq results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: CartPole-v1 type: CartPole-v1 metrics:...
[ -0.015233080834150314, 0.00019831128884106874, -0.0033474061638116837, 0.03647126257419586, 0.029079196974635124, -0.024798136204481125, -0.009188029915094376, -0.016188059002161026, -0.027745334431529045, 0.06241647154092789, -0.006842037662863731, -0.009775741957128048, -0.0131252547726035...
Azaghast/DistilBERT-SCP-Class-Classification
[ "pytorch", "distilbert", "text-classification", "transformers" ]
text-classification
{ "architectures": [ "DistilBertForSequenceClassification" ], "model_type": "distilbert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, ...
42
null
--- tags: - CartPole-v1 - deep-reinforcement-learning - reinforcement-learning - custom-implementation library_name: cleanrl model-index: - name: DQPN_freq results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: CartPole-v1 type: CartPole-v1 metrics:...
[ -0.015169813297688961, 0.00029037651256658137, -0.0028864885680377483, 0.036973293870687485, 0.028101347386837006, -0.02317674458026886, -0.009901993907988071, -0.01598571427166462, -0.028587546199560165, 0.06184187904000282, -0.005594628397375345, -0.009239028207957745, -0.01262865867465734...
Azaghast/GPT2-SCP-Descriptions
[ "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...
5
null
--- tags: - CartPole-v1 - deep-reinforcement-learning - reinforcement-learning - custom-implementation library_name: cleanrl model-index: - name: DQPN_freq results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: CartPole-v1 type: CartPole-v1 metrics:...
[ -0.016116255894303322, 0.00018549244850873947, -0.002547697862610221, 0.03686343878507614, 0.028021536767482758, -0.023564117029309273, -0.009003785438835621, -0.01614402048289776, -0.027964195236563683, 0.061254262924194336, -0.005454112309962511, -0.009108161553740501, -0.01194634474813938...
Azizun/Geotrend-10-epochs
[ "pytorch", "bert", "token-classification", "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...
6
null
--- tags: - CartPole-v1 - deep-reinforcement-learning - reinforcement-learning - custom-implementation library_name: cleanrl model-index: - name: DQN results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: CartPole-v1 type: CartPole-v1 metrics: -...
[ -0.01776508428156376, -0.0006539380992762744, 0.0012486563064157963, 0.032132476568222046, 0.031648676842451096, -0.024990975856781006, -0.015427902340888977, -0.017807509750127792, -0.028385119512677193, 0.062011439353227615, -0.008952852338552475, -0.003991414792835712, -0.0053748749196529...
BSC-LT/roberta-base-ca
[ "pytorch", "roberta", "fill-mask", "ca", "transformers", "masked-lm", "BERTa", "catalan", "license:apache-2.0", "autotrain_compatible" ]
fill-mask
{ "architectures": [ "RobertaForMaskedLM" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngra...
18
2023-03-20T20:01:38Z
--- license: mit tags: - feature-extraction library_name: fasttext language: mr widget: - text: apple example_title: apple --- # fastText (Marathi) fastText is an open-source, free, lightweight library that allows users to learn text representations and text classifiers. It works on standard, generic hardwar...
[ -0.00133539829403162, -0.030624203383922577, -0.031609661877155304, 0.05878257378935814, 0.017743291333317757, 0.051622793078422546, -0.009674126282334328, -0.016139278188347816, -0.020235443487763405, 0.04375666007399559, 0.02636677585542202, 0.01889292523264885, 0.014050483703613281, 0.0...
BSC-LT/roberta-large-bne-capitel-pos
[ "pytorch", "roberta", "token-classification", "es", "dataset:bne", "dataset:capitel", "arxiv:1907.11692", "arxiv:2107.07253", "transformers", "national library of spain", "spanish", "bne", "capitel", "pos", "license:apache-2.0", "autotrain_compatible" ]
token-classification
{ "architectures": [ "RobertaForTokenClassification" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_...
13
2023-03-20T20:05:21Z
--- license: mit tags: - feature-extraction library_name: fasttext language: mzn widget: - text: apple example_title: apple --- # fastText (Mazandarani) fastText is an open-source, free, lightweight library that allows users to learn text representations and text classifiers. It works on standard, generic ha...
[ -0.002836773172020912, -0.035159796476364136, -0.03074244223535061, 0.06856536865234375, 0.015419854782521725, 0.04721211642026901, -0.010340790264308453, -0.01792590506374836, -0.020789198577404022, 0.0422285832464695, 0.03081211820244789, 0.02403928153216839, 0.01263214647769928, 0.03199...
Babelscape/rebel-large
[ "pytorch", "safetensors", "bart", "text2text-generation", "en", "dataset:Babelscape/rebel-dataset", "transformers", "seq2seq", "relation-extraction", "license:cc-by-nc-sa-4.0", "model-index", "autotrain_compatible", "has_space" ]
text2text-generation
{ "architectures": [ "BartForConditionalGeneration" ], "model_type": "bart", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repe...
9,458
null
--- license: mit tags: - feature-extraction library_name: fasttext language: min widget: - text: apple example_title: apple --- # fastText (Minangkabau) fastText is an open-source, free, lightweight library that allows users to learn text representations and text classifiers. It works on standard, generic ha...
[ -0.0007286111358553171, -0.0341159962117672, -0.03219793364405632, 0.05822691321372986, 0.015548800118267536, 0.04395025223493576, -0.010496027767658234, -0.02006799355149269, -0.018756793811917305, 0.045041773468256, 0.026817042380571365, 0.02084980346262455, 0.011554162949323654, 0.03642...
Babysittingyoda/DialoGPT-small-familyguy
[ "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 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: validatio...
[ -0.02621736377477646, -0.002849662210792303, 0.007142852991819382, 0.018394671380519867, 0.02934986911714077, 0.025630230084061623, -0.023854313418269157, -0.011635221540927887, -0.023067932575941086, 0.05068933218717575, 0.020877817645668983, -0.04274272918701172, 0.01003609411418438, 0.0...
Badr/model1
[]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
2023-03-20T20:15:05Z
--- tags: - autotrain - vision - image-classification datasets: - davanstrien/autotrain-data-ia-test widget: - src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg example_title: Tiger - src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg example_title: Teap...
[ -0.012893578968942165, -0.021802563220262527, 0.01718280464410782, 0.04692963883280754, 0.05045503377914429, -0.00880417786538601, -0.013516999781131744, 0.0015088324435055256, -0.03871866688132286, 0.06389153003692627, -0.00010029669647337869, 0.0031363703310489655, 0.0038780884351581335, ...
Bagus/ser-japanese
[]
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: - autotrain - vision - image-classification datasets: - davanstrien/autotrain-data-ia-test widget: - src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg example_title: Tiger - src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg example_title: Teap...
[ -0.012889591977000237, -0.02167508192360401, 0.016089145094156265, 0.04792175069451332, 0.05007818341255188, -0.008330247364938259, -0.01336223166435957, 0.0019090290879830718, -0.03916344791650772, 0.06361616402864456, -0.0003761133411899209, 0.00236320192925632, 0.003194459481164813, 0.0...
Bagus/wav2vec2-large-xlsr-bahasa-indonesia
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "el", "dataset:common_voice_id_6.1", "transformers", "audio", "speech", "bahasa-indonesia", "license:apache-2.0" ]
automatic-speech-recognition
{ "architectures": [ "Wav2Vec2ForCTC" ], "model_type": "wav2vec2", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_s...
12
2023-03-20T20:15:28Z
--- tags: - autotrain - vision - image-classification datasets: - davanstrien/autotrain-data-ia-test widget: - src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg example_title: Tiger - src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg example_title: Teap...
[ -0.012111527845263481, -0.02191174030303955, 0.015384456142783165, 0.04771583527326584, 0.05104928836226463, -0.009305722080171108, -0.014329002238810062, 0.002090264344587922, -0.03924618288874626, 0.06330593675374985, -0.0008971070637926459, 0.002876133192330599, 0.003589657600969076, 0....
Bakkes/BakkesModWiki
[]
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: - feature-extraction library_name: fasttext language: xmf widget: - text: apple example_title: apple --- # fastText (Mingrelian) fastText is an open-source, free, lightweight library that allows users to learn text representations and text classifiers. It works on standard, generic har...
[ -0.004562223330140114, -0.03272230923175812, -0.031583625823259354, 0.062071848660707474, 0.012906413525342941, 0.046948645263910294, -0.008706996217370033, -0.020982414484024048, -0.019418541342020035, 0.04143086448311806, 0.024815654382109642, 0.024950524792075157, 0.01491575501859188, 0...