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
list
CLAck/indo-pure
[ "pytorch", "marian", "text2text-generation", "en", "id", "dataset:ALT", "transformers", "translation", "license:apache-2.0", "autotrain_compatible" ]
translation
{ "architectures": [ "MarianMTModel" ], "model_type": "marian", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
4
null
--- license: mit tags: - generated_from_trainer model-index: - name: predict-perception-bert-blame-concept 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. --> # pred...
[ -0.024469349533319473, 0.004757357761263847, -0.00041370734106749296, 0.0387609526515007, 0.024689409881830215, 0.00886446051299572, -0.015618495643138885, -0.008811247535049915, -0.024806762114167213, 0.05206408351659775, 0.02325003407895565, -0.02871076948940754, 0.008527957834303379, 0....
CLAck/vi-en
[ "pytorch", "marian", "text2text-generation", "en", "vi", "dataset:ALT", "transformers", "translation", "license:apache-2.0", "autotrain_compatible" ]
translation
{ "architectures": [ "MarianMTModel" ], "model_type": "marian", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
6
null
--- license: mit tags: - generated_from_trainer model-index: - name: predict-perception-bert-blame-none 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. --> # predict...
[ -0.028564194217324257, 0.0057334317825734615, -0.000900148181244731, 0.03856409713625908, 0.02691318653523922, 0.0034293218050152063, -0.01986021362245083, -0.004941453225910664, -0.029645398259162903, 0.05756509304046631, 0.021797649562358856, -0.02156788483262062, 0.014064161106944084, 0...
CLEE/CLEE
[]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
null
--- license: mit tags: - generated_from_trainer model-index: - name: predict-perception-bert-cause-human 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. --> # predic...
[ -0.031875696033239365, 0.0020349854603409767, -0.0010106174740940332, 0.04843254014849663, 0.030057493597269058, 0.01335929799824953, -0.028242187574505806, -0.019965168088674545, -0.02806643210351467, 0.0462280698120594, 0.02825911156833172, -0.026335397735238075, 0.010961592197418213, 0....
CLTL/MedRoBERTa.nl
[ "pytorch", "roberta", "fill-mask", "nl", "transformers", "license:mit", "autotrain_compatible" ]
fill-mask
{ "architectures": [ "RobertaForMaskedLM" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngra...
2,988
null
--- license: mit --- # PyAutoCode: GPT-2 based Python auto-code. PyAutoCode is a cut-down python autosuggestion built on **GPT-2** *(motivation: GPyT)* model. This baby model *(trained only up to 3 epochs)* is not **"fine-tuned"** yet therefore, I highly recommend not to use it in a production environment or in...
[ -0.012699154205620289, -0.01991746574640274, -0.004389551468193531, 0.05391748249530792, 0.024294693022966385, 0.031359653919935226, -0.012315075844526291, 0.003592779627069831, -0.017590859904885292, 0.05048098787665367, 0.033175285905599594, 0.0033051432110369205, 0.016554908826947212, 0...
CLTL/gm-ner-xlmrbase
[ "pytorch", "tf", "xlm-roberta", "token-classification", "nl", "transformers", "dighum", "license:apache-2.0", "autotrain_compatible" ]
token-classification
{ "architectures": [ "XLMRobertaForTokenClassification" ], "model_type": "xlm-roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, ...
2
null
--- license: mit tags: - generated_from_trainer model-index: - name: predict-perception-bert-cause-object 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. --> # predi...
[ -0.027738967910408974, 0.003960146103054285, 0.0008444736595265567, 0.04312693700194359, 0.02422327920794487, 0.012251487001776695, -0.016896506771445274, -0.014097169041633606, -0.029191141948103905, 0.04801338538527489, 0.027627620846033096, -0.02657472714781761, 0.008361089043319225, 0....
CLTL/icf-domains
[ "pytorch", "roberta", "nl", "transformers", "license:mit", "text-classification" ]
text-classification
{ "architectures": [ "RobertaForMultiLabelSequenceClassification" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": nul...
35
null
--- license: mit tags: - generated_from_trainer model-index: - name: predict-perception-bert-cause-concept 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. --> # pred...
[ -0.02769280970096588, 0.0024609374813735485, -0.0012166444212198257, 0.03925178572535515, 0.023301606997847557, 0.010716027580201626, -0.023821545764803886, -0.014789659529924393, -0.030008427798748016, 0.046860288828611374, 0.028222868219017982, -0.027052875608205795, 0.006673017051070929, ...
CLTL/icf-levels-adm
[ "pytorch", "roberta", "text-classification", "nl", "transformers", "license:mit" ]
text-classification
{ "architectures": [ "RobertaForSequenceClassification" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "...
33
null
--- license: mit tags: - generated_from_trainer model-index: - name: predict-perception-bert-cause-none 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. --> # predict...
[ -0.03375721722841263, -0.000394510047044605, -0.004486399702727795, 0.03996264934539795, 0.027860432863235474, 0.010725379921495914, -0.026394419372081757, -0.015587753616273403, -0.03635789453983307, 0.05156537517905235, 0.026468120515346527, -0.03416057676076889, 0.007451069541275501, 0....
CLTL/icf-levels-ber
[ "pytorch", "roberta", "text-classification", "nl", "transformers", "license:mit" ]
text-classification
{ "architectures": [ "RobertaForSequenceClassification" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "...
33
null
--- tags: - conversational --- # Handsome Jack DialoGPT Model
[ -0.03750694915652275, 0.0318681076169014, 0.014977330341935158, 0.017665909603238106, 0.01384120061993599, 0.015519542619585991, 0.002865513553842902, 0.031871527433395386, -0.006554714869707823, 0.021357085555791855, 0.017471570521593094, -0.04337666556239128, 0.015711165964603424, 0.0333...
CLTL/icf-levels-etn
[ "pytorch", "roberta", "text-classification", "nl", "transformers", "license:mit" ]
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, "...
31
null
--- license: mit tags: - generated_from_trainer model-index: - name: predict-perception-bert-focus-victim 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. --> # predi...
[ -0.03140510246157646, -0.01729723811149597, -0.004688826855272055, 0.0372045673429966, 0.02358311600983143, 0.018643202260136604, -0.014324159361422062, -0.03412604331970215, -0.012866692617535591, 0.047176871448755264, 0.03390176221728325, -0.026847371831536293, 0.029239758849143982, 0.05...
CLTL/icf-levels-ins
[ "pytorch", "roberta", "text-classification", "nl", "transformers", "license:mit" ]
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, "...
32
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 args: default...
[ -0.008759183809161186, 0.009355749934911728, -0.02890782244503498, 0.03778859227895737, 0.0607081763446331, 0.033975474536418915, -0.023836228996515274, -0.03574742004275322, -0.03384697437286377, 0.056004997342824936, 0.019233083352446556, -0.04703758656978607, 0.03486902639269829, 0.0431...
CLTL/icf-levels-stm
[ "pytorch", "roberta", "text-classification", "nl", "transformers", "license:mit" ]
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, "...
32
null
--- tags: - summarization - generated_from_trainer metrics: - rouge model-index: - name: bart-large-cnn-samsum-rescom-finetuned-resume-summarizer-9-epoch-tweak results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread a...
[ -0.0014964084839448333, -0.0011873896000906825, -0.005787521135061979, 0.0259346142411232, 0.035620346665382385, -0.0034860167652368546, -0.03398576006293297, -0.009940075688064098, -0.04986505210399628, 0.06341677159070969, 0.05018799751996994, -0.02040342427790165, 0.01240544207394123, 0...
CNT-UPenn/Bio_ClinicalBERT_for_seizureFreedom_classification
[ "pytorch", "bert", "text-classification", "transformers" ]
text-classification
{ "architectures": [ "BertForSequenceClassification" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_rep...
28
null
--- license: apache-2.0 tags: - generated_from_trainer model-index: - name: wav2vec2-large-xls-r-300m-german-with-lm results: [] --- # wav2vec2-large-xls-r-300m-german-with-lm This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the German set ...
[ -0.04200496897101402, -0.003088044933974743, -0.012010913342237473, 0.05585036426782608, 0.04825352132320404, 0.028468796983361244, -0.015660038217902184, -0.0024209024850279093, -0.02737640216946602, 0.05512692779302597, 0.026877595111727715, -0.011264068074524403, -0.004490616265684366, ...
Caddy/UD
[]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
null
--- language: en thumbnail: http://www.huggingtweets.com/atarifounders/1648266306699/predictions.png tags: - huggingtweets widget: - text: "My dream is" --- <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:inherit; margin-left: 4px; margin-right: 4px; w...
[ -0.0003882679739035666, -0.04204742610454559, -0.002426691586151719, 0.05190938338637352, 0.05670718103647232, 0.011694385670125484, -0.014132042415440083, -0.01559656672179699, -0.04544816538691521, 0.03405921906232834, 0.012662850320339203, -0.002341165207326412, -0.010555986315011978, 0...
Callidior/bert2bert-base-arxiv-titlegen
[ "pytorch", "safetensors", "encoder-decoder", "text2text-generation", "en", "dataset:arxiv_dataset", "transformers", "summarization", "license:apache-2.0", "autotrain_compatible", "has_space" ]
summarization
{ "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...
145
null
--- tags: - generated_from_trainer datasets: - pub_med_summarization_dataset metrics: - rouge model-index: - name: pegasus-cnn_dailymail-finetuned-pubmed results: - task: name: Sequence-to-sequence Language Modeling type: text2text-generation dataset: name: pub_med_summarization_dataset ...
[ -0.014486664906144142, -0.027868736535310745, -0.009850425645709038, 0.04674763232469559, 0.050473373383283615, 0.0028363587334752083, -0.024196133017539978, -0.03736850991845131, -0.021115800365805626, 0.055931735783815384, 0.02192257158458233, -0.006893084850162268, -0.0019330590730533004,...
CalvinHuang/mt5-small-finetuned-amazon-en-es
[ "pytorch", "tensorboard", "mt5", "text2text-generation", "transformers", "summarization", "generated_from_trainer", "license:apache-2.0", "autotrain_compatible" ]
summarization
{ "architectures": [ "MT5ForConditionalGeneration" ], "model_type": "mt5", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat...
16
null
## bert-base-uncased finetuned on IMDB dataset Evaluation set was created by taking 1000 samples from test set ``` DatasetDict({ train: Dataset({ features: ['text', 'label'], num_rows: 25000 }) dev: Dataset({ features: ['text', 'label'], num_rows: 1000 }) test: Data...
[ -0.006797319278120995, -0.008830633014440536, -0.02086758427321911, 0.05152638256549835, 0.041637469083070755, 0.009005743078887463, -0.02307341806590557, -0.02036019042134285, -0.024504946544766426, 0.048273716121912, 0.016777463257312775, -0.03579966351389885, 0.012866211123764515, 0.046...
Cameron/BERT-SBIC-offensive
[ "pytorch", "jax", "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
--- tags: - conversational --- # My Awesome Model
[ -0.048466309905052185, 0.00276248250156641, -0.0015600514598190784, 0.010406834073364735, 0.0019493288127705455, 0.023424038663506508, -0.004107934422791004, 0.01842644065618515, -0.014749204739928246, 0.03407078608870506, 0.047987498342990875, 0.007490057498216629, 0.0043542468920350075, ...
Cameron/BERT-eec-emotion
[ "pytorch", "jax", "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...
36
null
--- tags: - generated_from_trainer datasets: - librispeech_asr model-index: - name: '' 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. --> # This model was trained...
[ -0.014471860602498055, -0.004903964698314667, -0.0258083026856184, 0.04962216690182686, 0.03152959421277046, 0.012106824666261673, -0.01078029815107584, -0.015412948094308376, -0.054845117032527924, 0.06385225802659988, 0.026019122451543808, -0.024844497442245483, 0.006785520818084478, 0.0...
Cameron/BERT-jigsaw-identityhate
[ "pytorch", "jax", "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...
37
null
{ 'max_seq_length': 384, 'batch_size': 24, 'learning_rate': {'val': 3e-5, 'schelduler': 'Linear'}, 'max_clip_norm': None, 'epochs': 2 }
[ -0.04293996840715408, 0.003561923047527671, -0.0012882363516837358, 0.0267332773655653, 0.04215828329324722, -0.00912842620164156, -0.005994075443595648, -0.011461050249636173, -0.01623954437673092, 0.05801478400826454, 0.026814894750714302, -0.00037970420089550316, 0.01593359000980854, 0....
Cameron/BERT-jigsaw-severetoxic
[ "pytorch", "jax", "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...
30
null
--- tags: autonlp language: unk widget: - text: "I love AutoNLP 🤗" datasets: - spy24/autonlp-data-parrot_paraphrasing co2_eq_emissions: 0.8335491678002559 --- # Test
[ -0.02699464187026024, -0.018048040568828583, 0.0025100908242166042, 0.04269363358616829, 0.04362158104777336, 0.014674996957182884, 0.0009363047429360449, -0.008097585290670395, -0.024456661194562912, 0.0756104588508606, 0.03203233331441879, 0.02445238083600998, 0.013878298923373222, 0.023...
Cameron/BERT-mdgender-wizard
[ "pytorch", "jax", "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...
30
2022-03-11T00:09:35Z
--- language: en license: apache-2.0 --- HF-version model for PRIMERA: Pyramid-based Masked Sentence Pre-training for Multi-document Summarization (ACL 2022). The original code can be found [here](https://github.com/allenai/PRIMER). You can find the script and notebook to train/evaluate the model in ...
[ -0.01708548329770565, -0.04458912834525108, 0.00351477088406682, 0.05246971175074577, 0.03445760905742645, 0.0013561610830947757, -0.031937502324581146, -0.026671152561903, -0.03691129386425018, 0.06351368129253387, 0.017586978152394295, -0.007909492589533329, -0.0021917964331805706, 0.038...
Camzure/MaamiBot-test
[ "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...
9
null
--- language: en license: apache-2.0 --- HF-version model for PRIMERA: Pyramid-based Masked Sentence Pre-training for Multi-document Summarization (ACL 2022). The original code can be found [here](https://github.com/allenai/PRIMER). You can find the script and notebook to train/evaluate the model in ...
[ -0.018754668533802032, -0.04782060533761978, 0.0008578050183132291, 0.05415429547429085, 0.041258569806814194, 0.004440325312316418, -0.028301073238253593, -0.031263548880815506, -0.03449775651097298, 0.06634917855262756, 0.01608210988342762, -0.005881614051759243, -0.0005980181158520281, ...
Canadiancaleb/DialoGPT-small-jesse
[ "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...
9
null
--- license: apache-2.0 --- HF-version model for PRIMERA: Pyramid-based Masked Sentence Pre-training for Multi-document Summarization (ACL 2022). The original code can be found [here](https://github.com/allenai/PRIMER). You can find the script and notebook to train/evaluate the model in the original github rep...
[ -0.02040060982108116, -0.04667118936777115, 0.0010539350332692266, 0.05291629955172539, 0.03910449519753456, 0.0031601437367498875, -0.02711232751607895, -0.02959975227713585, -0.032210834324359894, 0.06380854547023773, 0.017574435099959373, -0.0035182528663426638, 0.0027646252419799566, 0...
Canadiancaleb/DialoGPT-small-walter
[ "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
--- tags: - generated_from_trainer model-index: - name: gpt2-xl-fine-tuned-debiased 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. --> # gpt2-xl-fine-tuned-debiased...
[ -0.02176857180893421, -0.0033960279542952776, 0.007952417246997356, 0.03510742262005806, 0.036265984177589417, 0.016623862087726593, -0.001770006725564599, 0.0013129061553627253, -0.03630475699901581, 0.039719004184007645, 0.015763763338327408, -0.026009585708379745, 0.006045945920050144, ...
Canyonevo/DialoGPT-medium-KingHenry
[]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
null
--- license: mit tags: - generated_from_trainer metrics: - f1 model-index: - name: xlm-roberta-base-finetuned-panx-de-fr 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 commen...
[ -0.03630080446600914, -0.014896714128553867, 0.003891392145305872, 0.02958679012954235, 0.02350511960685253, 0.021707214415073395, -0.01792687550187111, -0.0074071502313017845, -0.02978663146495819, 0.04548173397779465, 0.024457551538944244, -0.051930565387010574, 0.009754955768585205, 0.0...
CapitainData/wav2vec2-large-xlsr-turkish-demo-colab
[]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
null
--- license: mit tags: - generated_from_trainer datasets: - xtreme metrics: - f1 model-index: - name: xlm-roberta-base-finetuned-panx-fr results: - task: name: Token Classification type: token-classification dataset: name: xtreme type: xtreme args: PAN-X.fr metrics: - name:...
[ -0.022534744814038277, -0.005451971665024757, 0.0025212399195879698, 0.018574342131614685, 0.0281607024371624, 0.020810741931200027, -0.025394802913069725, -0.013964601792395115, -0.016840234398841858, 0.045851994305849075, 0.01920722983777523, -0.04265077784657478, 0.009676409885287285, 0...
Capreolus/bert-base-msmarco
[ "pytorch", "tf", "jax", "bert", "text-classification", "arxiv:2008.09093", "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...
238
null
--- license: mit tags: - generated_from_trainer datasets: - xtreme metrics: - f1 model-index: - name: xlm-roberta-base-finetuned-panx-it results: - task: name: Token Classification type: token-classification dataset: name: xtreme type: xtreme args: PAN-X.it metrics: - name:...
[ -0.024096816778182983, -0.001230237539857626, 0.004518392961472273, 0.01949974149465561, 0.027141185477375984, 0.022341514006257057, -0.017833776772022247, -0.00973468367010355, -0.01538517139852047, 0.04417481645941734, 0.024959120899438858, -0.04596196860074997, 0.01821575127542019, 0.03...
Capreolus/electra-base-msmarco
[ "pytorch", "tf", "electra", "text-classification", "arxiv:2008.09093", "transformers" ]
text-classification
{ "architectures": [ "ElectraForSequenceClassification" ], "model_type": "electra", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "...
110
null
--- language: - "de" tags: - "german" - "token-classification" - "pos" - "dependency-parsing" datasets: - "universal_dependencies" license: "mit" pipeline_tag: "token-classification" --- # bert-large-german-upos ## Model Description This is a BERT model pre-trained with [UD_German-HDT](https://github.com/UniversalDe...
[ -0.019034774973988533, -0.020398981869220734, -0.0075975744985044, 0.03744429722428322, 0.02887812629342079, 0.048731543123722076, -0.014959970489144325, -0.007379650138318539, -0.019795449450612068, 0.08017479628324509, 0.0039726984687149525, -0.0050467816181480885, 0.01566787250339985, 0...
Captain-1337/CrudeBERT
[ "pytorch", "bert", "text-classification", "arxiv:1908.10063", "transformers" ]
text-classification
{ "architectures": [ "BertForSequenceClassification" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_rep...
28
null
--- license: mit tags: - generated_from_trainer metrics: - f1 model-index: - name: xlm-roberta-base-finetuned-panx-all results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment....
[ -0.042194440960884094, -0.009863943792879581, 0.0038176148664206266, 0.032704878598451614, 0.02282145246863365, 0.02398330345749855, -0.017159478738904, -0.004166330676525831, -0.027559110894799232, 0.04839472100138664, 0.026422908529639244, -0.049982666969299316, 0.022377725690603256, 0.0...
Captain272/lstm
[]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
null
--- language: Thai task: extractive question answering datasets: xquad.th tags: - bert-base --- # Model Description This model is for Thai extractive question answering. It is based on the multilingual BERT [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) model, and it is case-sen...
[ -0.016450827941298485, -0.02877294458448887, -0.00516305910423398, 0.05624663457274437, 0.021125350147485733, 0.014940050430595875, -0.019598977640271187, -0.01035369373857975, -0.039192087948322296, 0.03773586452007294, 0.018066151067614555, 0.007968680001795292, -0.004671319853514433, 0....
Carlork314/Xd
[]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
null
--- language: Malay task: extractive question answering datasets: Malay SQuAD tags: - bert-base --- # Model Description This model is for Malay extractive question answering. It is based on the [malay-huggingface/bert-base-bahasa-cased](https://huggingface.co/malay-huggingface/bert-base-bahasa-cased/tree/main) model...
[ -0.010666994377970695, -0.040676724165678024, -0.01218459103256464, 0.051014434546232224, 0.031647782772779465, 0.01539635844528675, -0.018195971846580505, -0.015490037389099598, -0.036074213683605194, 0.05207157880067825, 0.02224082499742508, 0.0036768263671547174, -0.006197939161211252, ...
CarlosTron/Yo
[]
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: - conversational --- # willem DialoGPT Model
[ -0.033825475722551346, 0.014881577342748642, 0.01045114267617464, 0.008587697520852089, 0.023410579189658165, 0.027111127972602844, -0.002444775775074959, 0.021760590374469757, -0.011768064461648464, 0.02240094356238842, 0.03225504606962204, -0.03893258795142174, 0.005118108354508877, 0.03...
dccuchile/albert-base-spanish-finetuned-qa-mlqa
[ "pytorch", "albert", "question-answering", "transformers", "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...
3
null
--- license: cc0-1.0 tags: - automatic-speech-recognition - NbAiLab/NPSC - generated_from_trainer model-index: - name: '' 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 comme...
[ -0.04320521280169487, -0.011456168256700039, -0.00887607503682375, 0.0314500518143177, 0.03645351529121399, 0.012520916759967804, 0.010555990971624851, -0.008953362703323364, -0.021275462582707405, 0.04270947352051735, 0.0200656671077013, -0.031642138957977295, 0.012022801674902439, 0.0434...
dccuchile/albert-tiny-spanish-finetuned-mldoc
[ "pytorch", "albert", "text-classification", "transformers" ]
text-classification
{ "architectures": [ "AlbertForSequenceClassification" ], "model_type": "albert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no...
32
null
--- language: - code license: mit datasets: - anjandash/java-8m-methods-v1 ---
[ -0.03625337779521942, -0.011234967969357967, -0.006367281544953585, 0.006554165855050087, 0.04454168304800987, 0.0275256484746933, -0.0021247470285743475, 0.015030321665108204, -0.021060384809970856, 0.039958126842975616, 0.02511710859835148, -0.008813383989036083, 0.0621023066341877, 0.04...
dccuchile/albert-tiny-spanish-finetuned-ner
[ "pytorch", "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
null
This repo contains model for [Data-to-text Generation with Variational Sequential Planning](https://arxiv.org/abs/2202.13756) (Ratish Puduppully and Yao Fu and Mirella Lapata; In Transactions of the Association for Computational Linguistics (TACL)). This model is trained on the [MLB dataset](https://huggingface.co/d...
[ -0.024853508919477463, -0.008423148654401302, -0.010387085378170013, 0.07529138028621674, 0.031214212998747826, 0.029833633452653885, 0.0053390320390462875, -0.006654317025095224, -0.007999892346560955, 0.03174056485295296, 0.04620468243956566, -0.0037005525082349777, 0.0022724405862390995, ...
dccuchile/albert-tiny-spanish-finetuned-pawsx
[ "pytorch", "albert", "text-classification", "transformers" ]
text-classification
{ "architectures": [ "AlbertForSequenceClassification" ], "model_type": "albert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no...
29
null
--- license: mit --- CER: 0.0019 training code https://colab.research.google.com/drive/14MfFkhgPS63RJcP7rpBOK6OII_y34jx_?usp=sharing
[ -0.04756081849336624, -0.0179695263504982, -0.004077109973877668, 0.022598128765821457, 0.04463604465126991, 0.008268335834145546, -0.0018670036224648356, 0.007453978061676025, -0.04732662811875343, 0.02816365472972393, 0.022677965462207794, 0.0012764143757522106, 0.01791398599743843, 0.03...
dccuchile/albert-tiny-spanish-finetuned-pos
[ "pytorch", "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...
5
null
This repo contains model for [Data-to-text Generation with Variational Sequential Planning](https://arxiv.org/abs/2202.13756) (Ratish Puduppully and Yao Fu and Mirella Lapata; In Transactions of the Association for Computational Linguistics (TACL)). This model is trained on the [RotoWire dataset](https://github.com/...
[ -0.0232747420668602, -0.005820234771817923, -0.003992275334894657, 0.07508844137191772, 0.027740169316530228, 0.0326874703168869, -0.0010358330328017473, 0.004644630942493677, -0.010495506227016449, 0.035611577332019806, 0.043122872710227966, -0.005670292768627405, -0.003932393621653318, 0...
dccuchile/albert-tiny-spanish-finetuned-xnli
[ "pytorch", "albert", "text-classification", "transformers" ]
text-classification
{ "architectures": [ "AlbertForSequenceClassification" ], "model_type": "albert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no...
31
null
This repo contains model for [Data-to-text Generation with Variational Sequential Planning](https://arxiv.org/abs/2202.13756) (Ratish Puduppully and Yao Fu and Mirella Lapata; In Transactions of the Association for Computational Linguistics (TACL)). This model is trained on the [German RotoWire dataset](https://hugg...
[ -0.021625401452183723, -0.006774604320526123, -0.01101631298661232, 0.0796852633357048, 0.029140254482626915, 0.03484732285141945, 0.004397344775497913, 0.0003449830401223153, -0.01404175627976656, 0.04694002494215965, 0.04694350063800812, -0.013912574388086796, -0.0028351577930152416, 0.0...
dccuchile/albert-xlarge-spanish-finetuned-ner
[ "pytorch", "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...
5
null
This model generate the math expression LATEX sequence according to the handwritten math expression image. in CROHME 2014 test dataset CER=0.507772718700326
[ -0.014676813036203384, -0.029100753366947174, 0.014321449212729931, 0.026886077597737312, 0.014236069284379482, 0.01059422455728054, 0.002902915235608816, -0.012633717618882656, 0.00098380574490875, 0.015331017784774303, 0.02262783609330654, -0.021177692338824272, -0.008543555624783039, 0....
dccuchile/albert-xlarge-spanish-finetuned-xnli
[ "pytorch", "albert", "text-classification", "transformers" ]
text-classification
{ "architectures": [ "AlbertForSequenceClassification" ], "model_type": "albert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no...
29
null
--- language: - ar tags: - AraGPT2 - GPT-2 - MSA - Arabic Text Summarization - Arabic News Title Generation - Arabic Paraphrasing widget: - text: "" --- # An Arabic abstractive text summarization model A fine-tuned AraGPT2 model on a dataset of 84,764 paragraph-summary pairs. More details on the fine-...
[ -0.003964496776461601, -0.026113705709576607, -0.03404639661312103, 0.07384014129638672, 0.047533586621284485, 0.01730894297361374, 0.00744857219979167, -0.011885973624885082, -0.03326650336384773, 0.07419068366289139, 0.01711844652891159, -0.004612601362168789, -0.007681405637413263, 0.03...
dccuchile/albert-xxlarge-spanish-finetuned-pos
[ "pytorch", "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...
3
null
--- license: apache-2.0 tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: roberta-base-biomedical-clinical-es-finetuned-ner-Concat_CRAFT_es results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You...
[ -0.027465669438242912, 0.006084282882511616, 0.0051898169331252575, 0.010964630171656609, 0.031078672036528587, 0.026490021497011185, -0.01727105863392353, -0.034863993525505066, -0.01886078156530857, 0.03542865067720413, 0.03272493928670883, -0.024824010208249092, 0.007087780628353357, 0....
dccuchile/bert-base-spanish-wwm-cased-finetuned-pawsx
[ "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...
25
null
--- language: mr license: cc-by-4.0 datasets: - L3Cube-MahaHate widget: - text: "I like you. </s></s> I love you." --- ## MahaHate-multi-RoBERTa MahaHate-multi-RoBERTa (Marathi Hate speech identification) is a MahaRoBERTa(l3cube-pune/marathi-roberta) model fine-tuned on L3Cube-MahaHate - a Marathi tweet-based hate ...
[ -0.025224365293979645, 0.0033153097610920668, -0.004703829530626535, 0.029701901599764824, 0.032598018646240234, 0.0601310059428215, -0.024511050432920456, -0.027634235098958015, -0.019308941438794136, 0.04335624352097511, 0.048227399587631226, -0.03271971270442009, 0.029849356040358543, 0...
dccuchile/bert-base-spanish-wwm-cased-finetuned-pos
[ "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...
1
null
--- tags: - generated_from_trainer datasets: - cnn_dailymail model-index: - name: albert_ernie_summarization_cnn_dailymail 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 comm...
[ -0.02759830839931965, -0.006442816462367773, -0.028435051441192627, 0.04820232465863228, 0.03588889166712761, 0.016780270263552666, -0.012195867486298084, -0.03539739549160004, -0.045748546719551086, 0.06164088100194931, 0.04660801962018013, -0.008243057876825333, 0.01776065118610859, 0.03...
dccuchile/bert-base-spanish-wwm-cased-finetuned-qa-mlqa
[ "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...
5
null
AI4Bharat's IndicBERT finetuned for few-shot transfer learning by fine-tuning on Hindi training data with Urdu validation and test sets. Expected low accuracy. Leverages mbert's tokenizer in this implementation. --- language: - ur tags: - named entity recognition - ner license: apache-2.0 datasets: - wikiann metrics:...
[ 0.007448236923664808, -0.0010850044200196862, -0.020020442083477974, 0.0301889069378376, 0.029399000108242035, 0.017594290897250175, -0.02062731608748436, -0.015034252777695656, -0.0375325083732605, 0.050043147057294846, 0.015091966837644577, -0.015143866650760174, 0.011459555476903915, 0....
dccuchile/bert-base-spanish-wwm-uncased-finetuned-ner
[ "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...
5
null
--- tags: - object-detection - COCO - YOLO - Darknet model-index: - name: moon results: - metrics: - type: mAP value: 1 name: mAP task: type: object-detection name: object-detection dataset: name: COCO type: COCO ---
[ -0.04501314088702202, -0.012477084994316101, 0.012728541158139706, -0.011374053545296192, 0.05124831572175026, 0.007231284864246845, -0.0008184682228602469, 0.019234618172049522, -0.020975084975361824, 0.06053522974252701, 0.051776934415102005, 0.01104168500751257, 0.01922689937055111, 0.0...
dccuchile/bert-base-spanish-wwm-uncased-finetuned-pos
[ "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...
5
null
--- language: en license: apache-2.0 --- ## ELECTRA for IF **ELECTRA** is a method for self-supervised language representation learning. They are trained to distinguish "real" input tokens vs "fake" input tokens generated by another neural network, similar to the discriminator of a [GAN](https://arxiv.org/pd...
[ -0.03923927992582321, -0.0031116714235395193, -0.0016301798168569803, 0.026300687342882156, 0.04223335161805153, 0.043062061071395874, -0.018732983618974686, -0.020224735140800476, -0.028767015784978867, 0.0412556417286396, 0.03385468199849129, 0.002040576422587037, -0.008038120344281197, ...
dccuchile/bert-base-spanish-wwm-uncased-finetuned-xnli
[ "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...
36
null
--- language: nl tags: - speech --- # Wav2Vec2-Dutch-Base A Dutch Wav2Vec2 model. This model is created by further pre-training the original English [`facebook/wav2vec2-base`](https://huggingface.co/facebook/wav2vec2-base) model on Dutch speech from [Het Corpus Gesproken Nederlands](https://taalmaterialen.ivdnt.org/d...
[ -0.04254467785358429, -0.02401842549443245, -0.009346178732812405, 0.032137662172317505, 0.03977691009640694, 0.03563184663653374, -0.006512810476124287, -0.015840761363506317, -0.03505690395832062, 0.055124372243881226, 0.02065141499042511, -0.029156804084777832, -0.0046283225528895855, 0...
dccuchile/distilbert-base-spanish-uncased-finetuned-ner
[ "pytorch", "distilbert", "token-classification", "transformers", "autotrain_compatible" ]
token-classification
{ "architectures": [ "DistilBertForTokenClassification" ], "model_type": "distilbert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, ...
28
null
--- pipeline_tag: sentence-similarity language: fr datasets: - stsb_multi_mt tags: - Text - Sentence Similarity - Sentence-Embedding - camembert-base license: apache-2.0 model-index: - name: sentence-camembert-base by Van Tuan DANG results: - task: name: Sentence-Embedding type: Text Similarity dat...
[ -0.022872816771268845, -0.02689649723470211, -0.009991868399083614, 0.0574314258992672, 0.034699320793151855, 0.03373033180832863, -0.02608996070921421, -0.0039985510520637035, -0.06155427545309067, 0.07441908866167068, 0.0028935365844517946, 0.0027507247868925333, -0.013261443004012108, 0...
dccuchile/distilbert-base-spanish-uncased-finetuned-pos
[ "pytorch", "distilbert", "token-classification", "transformers", "autotrain_compatible" ]
token-classification
{ "architectures": [ "DistilBertForTokenClassification" ], "model_type": "distilbert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, ...
3
null
--- language: ja license: cc-by-sa-4.0 tags: - finance widget: - text: 流動[MASK]は、1億円となりました。 --- # Additional pretrained BERT base Japanese finance This is a [BERT](https://github.com/google-research/bert) model pretrained on texts in the Japanese language. The codes for the pretraining are available at [reta...
[ 0.0010379592422395945, -0.04366583377122879, -0.005990390200167894, 0.03691248223185539, 0.026824023574590683, 0.03647107258439064, -0.000522522022947669, -0.018832847476005554, -0.032039936631917953, 0.05233220383524895, 0.03165186941623688, -0.018659597262740135, 0.027558015659451485, 0....
dccuchile/distilbert-base-spanish-uncased
[ "pytorch", "distilbert", "fill-mask", "es", "dataset:large_spanish_corpus", "transformers", "spanish", "OpenCENIA", "autotrain_compatible" ]
fill-mask
{ "architectures": [ "DistilBertForMaskedLM" ], "model_type": "distilbert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repea...
670
null
--- language: en tags: - question_answering datasets: - qasper --- # led-base for QA with qasper A 10 epochs train of [Longformer Encoder Decoder Baselines for Qasper](https://github.com/allenai/qasper-led-baseline). ## How to use ``` git clone https://github.com/allenai/qasper-led-baseline.git cd qasper-led-baselin...
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CennetOguz/distilbert-base-uncased-finetuned-recipe-accelerate
[ "pytorch", "distilbert", "fill-mask", "transformers", "autotrain_compatible" ]
fill-mask
{ "architectures": [ "DistilBertForMaskedLM" ], "model_type": "distilbert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repea...
7
null
--- license: apache-2.0 tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: Roberta-base-biomedical-clinical-es-finetuned-ner-CRAFT_en_es results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You sho...
[ -0.03796021640300751, 0.010457250289618969, 0.0049515594728291035, 0.018424974754452705, 0.04315299540758133, 0.022526325657963753, -0.015151372179389, -0.02360645681619644, -0.014577087946236134, 0.037156980484724045, 0.022112932056188583, -0.0031499075703322887, -0.012738145887851715, 0....
CennetOguz/distilbert-base-uncased-finetuned-recipe
[ "pytorch", "tensorboard", "distilbert", "fill-mask", "transformers", "generated_from_trainer", "license:apache-2.0", "autotrain_compatible" ]
fill-mask
{ "architectures": [ "DistilBertForMaskedLM" ], "model_type": "distilbert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repea...
2
null
--- tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: Biobert-base-cased-v1.2-finetuned-ner-CRAFT results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it...
[ -0.028885560110211372, 0.0112310154363513, -0.009282032027840614, 0.01648944988846779, 0.04177532345056534, 0.021324360743165016, -0.016432680189609528, -0.031265828758478165, -0.03100287914276123, 0.06388618052005768, 0.0243957731872797, -0.0009136826265603304, 0.015574318356812, 0.056884...
Chae/botman
[ "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...
5
null
--- tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: Biobert-base-cased-v1.2-finetuned-ner-CRAFT_es_en results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and compl...
[ -0.02946387603878975, 0.011883608996868134, -0.007050747983157635, 0.01993877813220024, 0.04270806163549423, 0.022557225078344345, -0.013052908703684807, -0.0281844362616539, -0.01767899841070175, 0.056351665407419205, 0.018934737890958786, 0.002984110964462161, 0.00009330113243777305, 0.0...
Chaewon/mmnt_decoder_en
[ "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...
12
2022-03-11T22:57:19Z
--- language: en thumbnail: https://github.com/borisdayma/huggingtweets/blob/master/img/logo.png?raw=true tags: - huggingtweets widget: - text: "My dream is" --- <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:inherit; margin-left: 4px; margin-right: 4...
[ 0.011339755728840828, -0.038650620728731155, -0.0018410335760563612, 0.038949280977249146, 0.050946421921253204, 0.013411362655460835, -0.025355931371450424, -0.009901294484734535, -0.034122493118047714, 0.037460315972566605, -0.003207764122635126, -0.009448299184441566, -0.00250279949977993...
Chaima/TunBerto
[]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
null
--- language: - multilingual - af - am - ar - ast - az - ba - be - bg - bn - br - bs - ca - ceb - cs - cy - da - de - el - en - es - et - fa - ff - fi - fr - fy - ga - gd - gl - gu - ha - he - hi - hr - ht - hu - hy - id - ig - ilo - is - it - ja - jv - ka - kk - km - kn - ko - lb - lg - ln - lo - lt - lv - mg - mk - ...
[ -0.04027411714196205, -0.01582718826830387, 0.00135868601500988, 0.06575606018304825, 0.0430949330329895, 0.034238267689943314, -0.008683254942297935, -0.010726404376327991, -0.03854519873857498, 0.036936063319444656, 0.012306231074035168, -0.025899702683091164, 0.00030391855398193, 0.0492...
chainyo/speaker-recognition-meetup
[]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
1
null
--- language: - es tags: - pytorch - causal-lm license: apache-2.0 datasets: - bertin-project/mc4-es-sampled --- - [✨Version v1✨](https://huggingface.co/bertin-project/bertin-gpt-j-6B/tree/v1): August 25th, 2022 (*[full](https://huggingface.co/bertin-project/bertin-gpt-j-6B/tree/v1) and [half-precision weights](https...
[ -0.011496271938085556, -0.001953141763806343, -0.00984277669340372, 0.03074195422232151, 0.029109032824635506, 0.013026710599660873, -0.017064619809389114, -0.005776568781584501, -0.041828420013189316, 0.039933063089847565, -0.0016800437588244677, -0.030379248782992363, 0.023128675296902657,...
Chalponkey/DialoGPT-small-Barry
[ "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
Deberta large trained on slue transcriptions for 50 epochs, lr = 5e-6
[ -0.010394656099379063, -0.002791442209854722, 0.023377995938062668, 0.021548492833971977, 0.06323670595884323, 0.015235109254717827, -0.018740013241767883, -0.01808524876832962, -0.038939766585826874, 0.026149580255150795, -0.003277770010754466, -0.05490099638700485, 0.014727955684065819, ...
CharlieChen/feedback-bigbird
[]
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 model-index: - name: reverse_text_generation_HarryPotter 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. --> #...
[ -0.011016192846000195, -0.008727487176656723, -0.022932471707463264, 0.05664663761854172, 0.030556829646229744, 0.028034081682562828, -0.0014002089155837893, -0.03270510584115982, -0.04587140306830406, 0.04808173328638077, 0.035764429718256, -0.028869666159152985, 0.01766796223819256, 0.03...
ChauhanVipul/BERT
[]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
null
--- language: "en" tags: - icefall - k2 - transducer - librispeech - ASR - stateless transducer - PyTorch - RNN-T - pruned RNN-T - speech recognition license: "apache-2.0" datasets: - librispeech metrics: - WER --- # Introduction This repo contains pre-trained model using <https://github.com/k2-fsa/icefall/pull/248>...
[ -0.035826053470373154, -0.02344772405922413, -0.005091161001473665, 0.04413037374615669, 0.055192239582538605, -0.017319854348897934, -0.010335972532629967, -0.004829127341508865, -0.06644893437623978, 0.06115676462650299, 0.005222612991929054, -0.007461403496563435, 0.012297792360186577, ...
Cheapestmedsshop/Buymodafinilus
[]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
null
--- language: - en license: apache-2.0 tags: - bart - biobart - biomedical inference: true widget: - text: "Influenza is a <mask> disease." - type: "text-generation" --- Paper: [BioBART: Pretraining and Evaluation of A Biomedical Generative Language Model](https://arxiv.org/pdf/2204.03905.pdf) ``` @misc{BioBAR...
[ -0.013580692000687122, -0.027913887053728104, -0.009122468531131744, 0.04512485861778259, 0.021454008296132088, 0.03219607099890709, -0.004660033155232668, -0.011653841473162174, -0.006816546432673931, 0.05380226671695709, 0.021601911634206772, -0.0076979766599833965, 0.021213917061686516, ...
Cheatham/xlm-roberta-base-finetuned
[ "pytorch", "xlm-roberta", "text-classification", "transformers" ]
text-classification
{ "architectures": [ "XLMRobertaForSequenceClassification" ], "model_type": "xlm-roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, ...
20
null
--- language: - en license: apache-2.0 tags: - bart - biobart - biomedical inference: true widget: - text: "Influenza is a <mask> disease." - type: "text-generation" --- Paper: [BioBART: Pretraining and Evaluation of A Biomedical Generative Language Model](https://arxiv.org/pdf/2204.03905.pdf) ``` @misc{BioBAR...
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CleveGreen/JobClassifier_v2_gpt
[ "pytorch", "gpt2", "text-classification", "transformers" ]
text-classification
{ "architectures": [ "GPT2ForSequenceClassification" ], "model_type": "gpt2", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_rep...
27
null
--- license: apache-2.0 tags: - generated_from_trainer metrics: - f1 model-index: - name: xtreme_s_xlsr_minds14 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. --> #...
[ -0.040282782167196274, -0.0018712285673245788, -0.025083055719733238, 0.023985544219613075, 0.032081522047519684, 0.024407682940363884, -0.01830202341079712, -0.0034013781696558, -0.014550654217600822, 0.048446621745824814, 0.034331075847148895, -0.018512200564146042, 0.008587315678596497, ...
CodeNinja1126/bert-q-encoder
[ "pytorch" ]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
3
2022-03-13T03:42:26Z
--- 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 args: default...
[ -0.009311536327004433, 0.009862136095762253, -0.02873067557811737, 0.038543205708265305, 0.060508135706186295, 0.033245641738176346, -0.024313578382134438, -0.03549429029226303, -0.03369568660855293, 0.05557684600353241, 0.01970086246728897, -0.04633151739835739, 0.034716926515102386, 0.04...
CodeNinja1126/xlm-roberta-large-kor-mrc
[ "pytorch", "xlm-roberta", "question-answering", "transformers", "autotrain_compatible" ]
question-answering
{ "architectures": [ "XLMRobertaForQuestionAnswering" ], "model_type": "xlm-roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, ...
8
null
--- license: mit tags: - generated_from_trainer metrics: - rouge model-index: - name: bart-large-cnn-weaksup-100-NOpad-early results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this co...
[ -0.030313869938254356, -0.003941186238080263, -0.01318045798689127, 0.03963743522763252, 0.029160020872950554, -0.008570636622607708, -0.03473623842000961, -0.02714666724205017, -0.03920694813132286, 0.0648895874619484, 0.020755503326654434, -0.015226033516228199, 0.015199829824268818, 0.0...
CoderEFE/DialoGPT-marxbot
[ "pytorch", "gpt2", "text-generation", "transformers", "conversational", "has_space" ]
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 tags: - generated_from_trainer metrics: - rouge model-index: - name: bart-large-cnn-weaksup-1000-NOpad-early results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this c...
[ -0.029444102197885513, -0.0032774058636277914, -0.01325925998389721, 0.03870442509651184, 0.030316559597849846, -0.00875852257013321, -0.034493643790483475, -0.02611536718904972, -0.039084672927856445, 0.06421293318271637, 0.020896267145872116, -0.01607527583837509, 0.015494602732360363, 0...
CoderEFE/DialoGPT-medium-marx
[ "pytorch", "gpt2", "text-generation", "transformers" ]
text-generation
{ "architectures": [ "GPT2LMHeadModel" ], "model_type": "gpt2", "task_specific_params": { "conversational": { "max_length": 1000 }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
7
null
--- license: mit tags: - generated_from_trainer metrics: - rouge model-index: - name: bart-large-cnn-weaksup-10k-NOpad-early results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this co...
[ -0.02824648655951023, -0.004962296690791845, -0.012261120602488518, 0.03854503855109215, 0.030120715498924255, -0.00876104086637497, -0.03410515934228897, -0.025723285973072052, -0.038496337831020355, 0.0642838180065155, 0.021244315430521965, -0.0135110542178154, 0.015943659469485283, 0.04...
Venkatakrishnan-Ramesh/Text_gen
[]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
null
--- license: mit tags: - generated_from_trainer metrics: - rouge model-index: - name: bart-large-cnn-100-lit-evalMA-NOpad 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 comme...
[ -0.029412036761641502, -0.007513691671192646, -0.007460565771907568, 0.04400603100657463, 0.030862318351864815, 0.0024887705221772194, -0.03073718398809433, -0.0284823477268219, -0.038200151175260544, 0.051082395017147064, 0.02629866451025009, -0.022806063294410706, 0.0241080429404974, 0.0...
CoffeeAddict93/gpt2-medium-call-of-the-wild
[ "pytorch", "gpt2", "text-generation", "transformers" ]
text-generation
{ "architectures": [ "GPT2LMHeadModel" ], "model_type": "gpt2", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
14
null
--- language: - "ru" tags: - "russian" - "token-classification" - "pos" - "dependency-parsing" datasets: - "universal_dependencies" license: "cc-by-sa-4.0" pipeline_tag: "token-classification" --- # bert-base-russian-upos ## Model Description This is a BERT model pre-trained with [UD_Russian](https://universaldepend...
[ -0.018779626116156578, -0.028530675917863846, -0.014058329164981842, 0.03828851506114006, 0.040336690843105316, 0.04454519599676132, -0.00880424864590168, -0.005620233714580536, -0.037130001932382584, 0.077250175178051, 0.007187491282820702, -0.007702632807195187, 0.015053808689117432, 0.0...
CoffeeAddict93/gpt2-medium-modest-proposal
[ "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...
7
null
--- tags: autonlp language: en widget: - text: "I love AutoNLP 🤗" datasets: - DrishtiSharma/autonlp-data-Text-Classification-Catalonia-Independence-AutoNLP co2_eq_emissions: 3.622203603306694 --- # Model Trained Using AutoNLP - Problem type: Multi-class Classification - Model ID: 633018323 - CO2 Emissions (in grams)...
[ -0.012723910622298717, -0.026917623355984688, -0.002635940909385681, 0.038377828896045685, 0.03679098188877106, 0.018423831090331078, -0.023749206215143204, -0.010222370736300945, -0.04648319259285927, 0.08788644522428513, 0.026574574410915375, 0.0015156661393120885, -0.0084464680403471, 0...
CoffeeAddict93/gpt2-modest-proposal
[ "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...
12
null
--- language: - hi - en - multilingual license: cc-by-4.0 tags: - hi - en - codemix datasets: - L3Cube-HingCorpus - L3Cube-HingLID --- ## HingBERT-LID HingBERT-LID is a Hindi-English code-mixed language identification BERT model. It is a HingBERT model fine-tuned on L3Cube-HingLID dataset. <br> [dataset link] (https:/...
[ -0.012841371819376945, -0.022173302248120308, -0.015159179456532001, 0.032182104885578156, 0.04189077392220497, 0.04581126570701599, -0.01803399808704853, -0.019246047362685204, -0.0010711157228797674, 0.060189809650182724, 0.02880839630961418, -0.030566034838557243, 0.0039090667851269245, ...
ComCom/gpt2-large
[ "pytorch", "gpt2", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "GPT2Model" ], "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": nul...
1
null
--- license: mit tags: - generated_from_trainer metrics: - rouge model-index: - name: bart-large-cnn-weaksup-100-NOpad-early1 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this c...
[ -0.029775720089673996, -0.0038600710686296225, -0.013576202094554901, 0.04024609923362732, 0.028997724875807762, -0.008076260797679424, -0.03506877273321152, -0.025777898728847504, -0.039605192840099335, 0.06464269012212753, 0.0210586991161108, -0.015313263051211834, 0.01533418893814087, 0...
ComCom/gpt2-medium
[ "pytorch", "gpt2", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "GPT2Model" ], "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": nul...
5
null
--- license: mit tags: - generated_from_trainer metrics: - rouge model-index: - name: bart-large-cnn-weaksup-100-NOpad-early2 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this c...
[ -0.030304554849863052, -0.005025381222367287, -0.012039353139698505, 0.039326637983322144, 0.02983337640762329, -0.007777562364935875, -0.034449584782123566, -0.026378385722637177, -0.03927186131477356, 0.06381805986166, 0.020851243287324905, -0.01383146271109581, 0.01414695754647255, 0.04...
cometrain/neurotitle-rugpt3-small
[ "pytorch", "gpt2", "text-generation", "ru", "en", "dataset:All-NeurIPS-Papers-Scraper", "transformers", "Cometrain AutoCode", "Cometrain AlphaML", "license:mit" ]
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...
20
null
--- license: mit tags: - generated_from_trainer metrics: - rouge model-index: - name: bart-large-cnn-1000-lit-evalMA-NOpad 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 comm...
[ -0.02802729606628418, -0.006790038198232651, -0.007905765436589718, 0.04422919824719429, 0.030991995707154274, 0.0012885673204436898, -0.03108990006148815, -0.02736653760075569, -0.037813182920217514, 0.05113822966814041, 0.025472640991210938, -0.02225401997566223, 0.024840619415044785, 0....
Connorvr/BrightBot-small
[ "pytorch", "gpt2", "text-generation", "transformers", "conversational" ]
conversational
{ "architectures": [ "GPT2LMHeadModel" ], "model_type": "gpt2", "task_specific_params": { "conversational": { "max_length": 1000 }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
7
null
--- license: mit tags: - generated_from_trainer metrics: - rouge model-index: - name: bart-large-cnn-100-lit-evalMA-NOpad2 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 comm...
[ -0.02939559519290924, -0.009261309169232845, -0.006884966976940632, 0.04400470480322838, 0.031469445675611496, 0.002874534111469984, -0.02860894240438938, -0.027020541951060295, -0.03634481504559517, 0.05039342865347862, 0.024607861414551735, -0.019006898626685143, 0.023194078356027603, 0....
Connorvr/TeachingGen
[ "pytorch", "gpt2", "text-generation", "transformers", "generated_from_trainer", "license:mit" ]
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...
4
null
--- license: mit tags: - generated_from_trainer metrics: - rouge model-index: - name: bart-large-cnn-10k-lit-evalMA-NOpad 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 comme...
[ -0.02699991688132286, -0.008125491440296173, -0.0062517742626369, 0.04352628067135811, 0.031053194776177406, 0.0021958393044769764, -0.03053477220237255, -0.028099248185753822, -0.038045916706323624, 0.05188611522316933, 0.026630479842424393, -0.02124965563416481, 0.025691276416182518, 0.0...
ConstellationBoi/Oop
[]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
null
--- language: - "de" tags: - "qa" widget: - text: "" context: "" example_title: "Extractive QA" --- # GELECTRA-large-LegalQuAD ## Overview **Language model:** GELECTRA-large **Language:** German **Downstream-task:** Extractive QA **Training data:** German-legal-SQuAD **Eval data:** German-legal-SQuAD t...
[ 0.011579510755836964, -0.031237555667757988, 0.009635020978748798, 0.04236616939306259, 0.06767046451568604, 0.01986004039645195, -0.004345096182078123, -0.008216517977416515, -0.03137940913438797, 0.059984009712934494, 0.0003342237905599177, 0.00112282601185143, -0.009915098547935486, 0.0...
Contrastive-Tension/BERT-Base-NLI-CT
[ "pytorch", "tf", "jax", "bert", "fill-mask", "transformers", "autotrain_compatible" ]
fill-mask
{ "architectures": [ "BertForMaskedLM" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
9
null
--- tags: - generated_from_trainer model-index: - name: finetuned results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # finetuned This model is a fine-tuned version...
[ -0.0178446676582098, -0.01770620234310627, 0.0009278740035369992, 0.032366011291742325, 0.03923770412802696, 0.02182145044207573, -0.019759640097618103, -0.007780433166772127, -0.0459725558757782, 0.051645707339048386, 0.02895504981279373, -0.019043250009417534, 0.004808319732546806, 0.034...
Contrastive-Tension/BERT-Distil-CT-STSb
[ "pytorch", "tf", "distilbert", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "DistilBertModel" ], "model_type": "distilbert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngra...
1
2022-03-13T12:22:58Z
--- tags: - generated_from_trainer datasets: - korquad model-index: - name: komrc_train 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. --> # komrc_train This model...
[ -0.039404693990945816, -0.01192132942378521, -0.015202559530735016, 0.02678617276251316, 0.03230517357587814, -0.0006862761219963431, -0.01496201939880848, -0.009722350165247917, -0.03882398083806038, 0.04124591127038002, 0.012590581551194191, -0.03180745989084244, -0.0070867775939404964, ...
Contrastive-Tension/BERT-Large-CT-STSb
[ "pytorch", "tf", "jax", "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
--- license: apache-2.0 tags: - generated_from_trainer datasets: - sem_eval2010_task8 metrics: - accuracy model-index: - name: distilbert-base-uncased-finetuned-sem results: - task: name: Text Classification type: text-classification dataset: name: sem_eval2010_task8 type: sem_eval2010_t...
[ 0.005776909179985523, -0.005944864358752966, -0.03228604421019554, 0.039251796901226044, 0.04868762567639351, 0.026974905282258987, -0.03796038404107094, -0.033809613436460495, -0.03834598883986473, 0.07052105665206909, 0.02045656554400921, -0.00744602968916297, 0.013981189578771591, 0.040...
Contrastive-Tension/BERT-Large-CT
[ "pytorch", "tf", "jax", "bert", "fill-mask", "transformers", "autotrain_compatible" ]
fill-mask
{ "architectures": [ "BertForMaskedLM" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
5
null
--- license: apache-2.0 tags: - generated_from_trainer datasets: - common_voice model-index: - name: wav2vec2-large-xls-r-300m-hindi 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...
[ -0.035098008811473846, -0.013722305186092854, -0.02389955334365368, 0.03312229737639427, 0.04074792191386223, 0.034031566232442856, -0.003304865676909685, -0.002491629682481289, -0.012996364384889603, 0.04838171601295471, 0.039794497191905975, -0.018612118437886238, 0.011093288660049438, 0...
Cool/Demo
[]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
null
--- language: en thumbnail: http://www.huggingtweets.com/mikepompeo/1647181695747/predictions.png tags: - huggingtweets widget: - text: "My dream is" --- <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:inherit; margin-left: 4px; margin-right: 4px; widt...
[ 0.002061150735244155, -0.03853773698210716, 0.001954921055585146, 0.05346323922276497, 0.048378411680459976, 0.007831357419490814, -0.007933647371828556, -0.010974752716720104, -0.040164750069379807, 0.03480737656354904, 0.010534601286053658, 0.0012006068136543036, -0.01655147597193718, 0....
Coolhand/Sentiment
[]
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: - masked-auto-encoding - generated_from_trainer datasets: - image_folder model-index: - name: test_mae_flysheet results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, th...
[ -0.038715116679668427, -0.020017007365822792, 0.01957295648753643, 0.019291577860713005, 0.032214220613241196, 0.01424431148916483, -0.006524947006255388, -0.015378724783658981, -0.014808908104896545, 0.04285043850541115, 0.019041920080780983, -0.01097477599978447, 0.027619386091828346, 0....
Coverage/sakurajimamai
[]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
null
--- tags: - generated_from_trainer model-index: - name: NewModel 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. --> # NewModel This model is a fine-tuned version o...
[ -0.021522000432014465, -0.02390223741531372, -0.00783302541822195, 0.035728536546230316, 0.03848443552851677, 0.031793735921382904, -0.010283166542649269, -0.01637372188270092, -0.03610384464263916, 0.056437861174345016, 0.0193394236266613, -0.023431446403265, -0.002976359101012349, 0.0378...
Coyotl/DialoGPT-test2-arthurmorgan
[ "pytorch", "gpt2", "text-generation", "transformers", "conversational" ]
conversational
{ "architectures": [ "GPT2LMHeadModel" ], "model_type": "gpt2", "task_specific_params": { "conversational": { "max_length": 1000 }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
7
null
--- license: apache-2.0 tags: - generated_from_trainer datasets: - squad_v2 model-index: - name: distilbert-base-uncased-finetuned-squad results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then re...
[ -0.01880287565290928, -0.006236874032765627, -0.031998757272958755, 0.04820895567536354, 0.06008988991379738, 0.022967413067817688, -0.03177649527788162, 0.002597405109554529, -0.03390440717339516, 0.0502869077026844, 0.03582253307104111, -0.022302299737930298, 0.012486159801483154, 0.0474...
Coyotl/DialoGPT-test3-arthurmorgan
[ "conversational" ]
conversational
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
null
--- language: - en tags: - aspect-based-sentiment-analysis - lcf-bert license: mit datasets: - laptop14 (w/ augmentation) - restaurant14 (w/ augmentation) - restaurant16 (w/ augmentation) - ACL-Twitter (w/ augmentation) - MAMS (w/ augmentation) - Television (w/ augmentation) - TShirt (w/ augmentation) - ...
[ -0.022965358570218086, -0.023170361295342445, -0.005188160575926304, 0.04884583130478859, 0.027166446670889854, 0.023812780156731606, -0.01718815602362156, 0.010590877383947372, -0.03831717371940613, 0.06992843747138977, 0.019907191395759583, -0.02185945212841034, -0.0018540546298027039, 0...
CracklesCreeper/Piglin-Talks-Harry-Potter
[ "pytorch", "gpt2", "text-generation", "transformers", "conversational" ]
conversational
{ "architectures": [ "GPT2LMHeadModel" ], "model_type": "gpt2", "task_specific_params": { "conversational": { "max_length": 1000 }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
10
null
--- license: 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 args: default...
[ -0.008910754695534706, 0.009449505247175694, -0.02930529974400997, 0.037425778806209564, 0.06081687659025192, 0.03377329558134079, -0.02368381805717945, -0.03587066009640694, -0.03348596394062042, 0.05542251840233803, 0.02022237330675125, -0.046955473721027374, 0.03565000742673874, 0.04293...
Craftified/Bob
[]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
null
--- license: mit tags: - generated_from_trainer model-index: - name: gpt2-ft-with-non-challenging 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. --> # gpt2-ft-with-...
[ -0.018890580162405968, -0.014948363415896893, -0.004227112978696823, 0.035762958228588104, 0.021638739854097366, 0.022319721058011055, 0.0028408842626959085, 0.002964273327961564, -0.04479966685175896, 0.05183148384094238, 0.01945079118013382, -0.017776332795619965, 0.01342172920703888, 0....
Craig/paraphrase-MiniLM-L6-v2
[ "pytorch", "bert", "arxiv:1908.10084", "sentence-transformers", "feature-extraction", "sentence-similarity", "transformers", "license:apache-2.0" ]
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...
1,026
null
--- tags: - generated_from_trainer model-index: - name: gpt2-xl-ft-with-non-challenging 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. --> # gpt2-xl-ft-with-non-cha...
[ -0.024047961458563805, -0.010689670220017433, -0.0010846356162801385, 0.035948481410741806, 0.02935669757425785, 0.01943107508122921, -0.0022661855909973383, -0.004572916775941849, -0.037352826446294785, 0.048285987228155136, 0.02068106271326542, -0.024356642737984657, -0.0015087258070707321...
Crasher222/kaggle-comp-test
[ "pytorch", "bert", "text-classification", "en", "dataset:Crasher222/autonlp-data-kaggle-test", "transformers", "autonlp", "co2_eq_emissions" ]
text-classification
{ "architectures": [ "BertForSequenceClassification" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_rep...
29
null
--- language: - multilingual - af - am - ar - ast - az - ba - be - bg - bn - br - bs - ca - ceb - cs - cy - da - de - el - en - es - et - fa - ff - fi - fr - fy - ga - gd - gl - gu - ha - he - hi - hr - ht - hu - hy - id - ig - ilo - is - it - ja - jv - ka - kk - km - kn - ko - lb - lg - ln - lo - lt - lv - mg - mk - ...
[ -0.028047794476151466, -0.01546022854745388, 0.007663625758141279, 0.05878151208162308, 0.03699784725904465, 0.03446916863322258, -0.0039151753298938274, -0.004336065612733364, -0.04736318811774254, 0.04163442179560661, 0.011208225041627884, -0.028302034363150597, -0.0013652833877131343, 0...
CrayonShinchan/fine_tune_try_1
[]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
null
--- datasets: - IteraTeR_full_sent --- # IteraTeR PEGASUS model This model was obtained by fine-tuning [google/pegasus-large](https://huggingface.co/google/pegasus-large) on [IteraTeR-full-sent](https://huggingface.co/datasets/wanyu/IteraTeR_full_sent) dataset. Paper: [Understanding Iterative Revision from Human-Writ...
[ 0.016763364896178246, -0.02252042666077614, -0.008469420485198498, 0.06744906306266785, 0.016086965799331665, 0.023014292120933533, -0.01489099208265543, -0.007860020734369755, -0.0550701767206192, 0.0378369502723217, 0.029819652438163757, -0.018023362383246422, 0.04930169880390167, 0.0102...
CrisLeaf/generador-de-historias-de-tolkien
[ "pytorch", "gpt2", "text-generation", "transformers" ]
text-generation
{ "architectures": [ "GPT2LMHeadModel" ], "model_type": "gpt2", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
8
null
--- datasets: - IteraTeR_full_sent --- # IteraTeR RoBERTa model This model was obtained by fine-tuning [roberta-large](https://huggingface.co/roberta-large) on [IteraTeR-human-sent](https://huggingface.co/datasets/wanyu/IteraTeR_human_sent) dataset. Paper: [Understanding Iterative Revision from Human-Written Text](ht...
[ 0.008462122641503811, -0.01183263212442398, -0.010635489597916603, 0.07491806149482727, 0.017422402277588844, 0.025918710976839066, -0.015948571264743805, -0.01046925038099289, -0.04714683070778847, 0.03956014662981033, 0.04687078297138214, -0.021750615909695625, 0.04172799736261368, 0.022...
Cryptikdw/DialoGPT-small-rick
[ "pytorch", "gpt2", "text-generation", "transformers", "conversational" ]
conversational
{ "architectures": [ "GPT2LMHeadModel" ], "model_type": "gpt2", "task_specific_params": { "conversational": { "max_length": 1000 }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
7
null
--- language: - multilingual - af - am - ar - ast - az - ba - be - bg - bn - br - bs - ca - ceb - cs - cy - da - de - el - en - es - et - fa - ff - fi - fr - fy - ga - gd - gl - gu - ha - he - hi - hr - ht - hu - hy - id - ig - ilo - is - it - ja - jv - ka - kk - km - kn - ko - lb - lg - ln - lo - lt - lv - mg - mk - m...
[ -0.02813272923231125, -0.015858445316553116, 0.006958180572837591, 0.05965433269739151, 0.037641171365976334, 0.034854765981435776, -0.0030670175328850746, -0.0036226955708116293, -0.04759363457560539, 0.04215420037508011, 0.009780436754226685, -0.028446344658732414, -0.0005438780062831938, ...
Crystal/distilbert-base-uncased-finetuned-squad
[]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
2022-03-13T21:11:41Z
--- tags: - espnet - audio - automatic-speech-recognition language: noinfo datasets: - swbd license: cc-by-4.0 --- ## ESPnet2 ASR model ### `espnet/roshansh_asr_base_sp_conformer_swbd` This model was trained by roshansh-cmu using swbd recipe in [espnet](https://github.com/espnet/espnet/). ### Demo: How to use in E...
[ -0.038323622196912766, -0.003449373645707965, -0.03927799314260483, 0.02600100263953209, 0.05670584365725517, 0.022541800513863564, -0.008950095623731613, 0.01638110727071762, -0.07024639844894409, 0.06530467420816422, 0.024352429434657097, 0.007297208532691002, -0.00545332208275795, 0.012...
Cthyllax/DialoGPT-medium-PaladinDanse
[ "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: apache-2.0 tags: - generated_from_trainer datasets: - adversarial_qa model-index: - name: distilbert-base-uncased-finetuned-advers results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, ...
[ -0.02615114115178585, -0.00806137640029192, -0.03548815846443176, 0.04121190682053566, 0.06368445605039597, 0.0132194384932518, -0.0016267154132947326, -0.03371225297451019, -0.045610565692186356, 0.04139937460422516, 0.010762074962258339, -0.01914495974779129, 0.0032026006374508142, 0.052...
Culmenus/checkpoint-168500-finetuned-de-to-is_nr2
[]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
null
--- language: en thumbnail: http://www.huggingtweets.com/ayurastro/1647214031676/predictions.png tags: - huggingtweets widget: - text: "My dream is" --- <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:inherit; margin-left: 4px; margin-right: 4px; width...
[ 0.0026659867726266384, -0.041310522705316544, -0.000576266145799309, 0.04914693161845207, 0.055175140500068665, 0.0015075054252520204, -0.015272898599505424, -0.014040584675967693, -0.039974045008420944, 0.02783975563943386, 0.013041382655501366, 0.004398464225232601, -0.007275671232491732, ...
Culmenus/opus-mt-de-is-finetuned-de-to-is_35g65cc_2
[]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
2022-03-14T00:27:34Z
--- 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 args: default...
[ -0.009102685377001762, 0.00972637441009283, -0.02897355519235134, 0.037772178649902344, 0.06069952994585037, 0.03391539305448532, -0.024059070274233818, -0.036078520119190216, -0.03386934846639633, 0.0559234544634819, 0.019685929641127586, -0.04699109122157097, 0.03537794202566147, 0.04342...
Culmenus/opus-mt-de-is-finetuned-de-to-is_ekkicc
[]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
null
--- tags: - conversational --- # Peter from Your Boyfriend Game.
[ -0.04038133844733238, 0.01862199418246746, -0.005940264090895653, 0.013471579179167747, 0.011410713195800781, 0.0030805489514023066, -0.008196857757866383, 0.015135719440877438, -0.02272164449095726, 0.03536350280046463, 0.046369362622499466, -0.0035121547989547253, 0.02424835041165352, 0....
CurtisASmith/GPT-JRT
[]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
null
--- license: mit --- # GPT2-Chinese-Gulong ## Description 自[GPT2-Chinese](https://github.com/Morizeyao/GPT2-Chinese)开源模型涌现了很多有趣的模型。本模型受到LEE Meng的[直觀理解 GPT-2 語言模型並生成金庸武俠小說](https://leemeng.tw/gpt2-language-model-generate-chinese-jing-yong-novels.html)一文启发,在文中GPT2被证明能够较好地学习到金庸的风格并能较为通顺地续写。金古二人并为当代武侠巨擘,但两人的写作风格大相径庭。金庸重...
[ -0.021112997084856033, -0.02819753997027874, -0.0023609439376741648, 0.07861923426389694, 0.0450960211455822, 0.025382602587342262, 0.013084967620670795, -0.011237326078116894, -0.004115324933081865, 0.041953396052122116, 0.021353373304009438, -0.0007600276148878038, -0.002544717863202095, ...
CurtisBowser/DialoGPT-medium-sora-two
[ "pytorch", "conversational" ]
conversational
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
null
--- tags: - generated_from_trainer datasets: - glue metrics: - matthews_correlation model-index: - name: efl-finetuned-cola results: - task: name: Text Classification type: text-classification dataset: name: glue type: glue args: cola metrics: - name: Matthews Correlation ...
[ -0.018891526386141777, 0.003873406210914254, 0.007597615476697683, 0.03494632989168167, 0.05675467103719711, 0.023064548149704933, -0.03209223970770836, -0.01891016773879528, -0.053096357733011246, 0.05183805152773857, 0.02865315042436123, -0.004558852408081293, 0.02423871122300625, 0.0254...
CurtisBowser/DialoGPT-medium-sora
[ "pytorch", "gpt2", "text-generation", "transformers", "conversational" ]
conversational
{ "architectures": [ "GPT2LMHeadModel" ], "model_type": "gpt2", "task_specific_params": { "conversational": { "max_length": 1000 }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
7
null
--- license: apache-2.0 tags: - generated_from_trainer datasets: - glue metrics: - accuracy model-index: - name: bert-base-uncased-finetuned-sst2 results: - task: name: Text Classification type: text-classification dataset: name: glue type: glue args: sst2 metrics: - name: ...
[ -0.012528123334050179, 0.0004379416350275278, -0.018077213317155838, 0.04082229360938072, 0.06588874012231827, 0.022215625271201134, -0.014921732246875763, -0.022566091269254684, -0.041142042726278305, 0.06157805025577545, -0.0043176570907235146, -0.013858482241630554, 0.025595789775252342, ...
Cyrell/Cyrell
[]
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
2022-03-14T06:28:29Z
--- language: ko tags: - gpt2 license: cc-by-nc-sa-4.0 --- - This model forked from [skt/kogpt2-base-v2](https://huggingface.co/skt/kogpt2-base-v2). - You can use this model in [Teachable-NLP](https://ainize.ai/teachable-nlp). For more details: https://github.com/SKT-AI/KoGPT2
[ -0.027614807710051537, -0.01460465881973505, 0.020407777279615402, 0.027691932395100594, 0.043577101081609726, 0.009864875115454197, 0.015163403004407883, 0.03635113686323166, -0.04140458628535271, 0.0408007875084877, 0.002307203598320484, -0.0162355974316597, 0.012518630363047123, 0.01946...