modelId
stringlengths
4
81
tags
list
pipeline_tag
stringclasses
17 values
config
dict
downloads
int64
0
59.7M
first_commit
timestamp[ns, tz=UTC]
card
stringlengths
51
438k
embedding
list
Despin89/test
[]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
null
See logs at https://wandb.ai/yepster/long-byt5-tglobal-small
[ -0.043838419020175934, 0.00674106040969491, 0.007722621783614159, 0.02232859656214714, 0.025855179876089096, 0.01265712734311819, 0.0000831115830806084, -0.016803571954369545, -0.021991237998008728, 0.006866980344057083, 0.019890975207090378, -0.04375094175338745, 0.004993657115846872, 0.0...
Dev-DGT/food-dbert-multiling
[ "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, ...
17
null
--- license: apache-2.0 tags: - generated_from_trainer datasets: - imdb model-index: - name: finetuning-sentiment-model-3000-samples 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...
[ -0.028740273788571358, -0.008730897679924965, -0.027832893654704094, 0.038407716900110245, 0.034726619720458984, 0.03808227553963661, -0.01578717678785324, -0.008879760280251503, -0.042068399488925934, 0.06388692557811737, 0.04582424461841583, -0.023596415296196938, 0.02814183384180069, 0....
DevsIA/Devs_IA
[]
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
--- title: Double Hard Debiasing emoji: 👁 colorFrom: blue colorTo: pink sdk: gradio sdk_version: 3.1.1 app_file: app.py pinned: false license: mit --- Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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DicoTiar/wisdomfiy
[ "pytorch", "bert", "fill-mask", "transformers", "autotrain_compatible" ]
fill-mask
{ "architectures": [ "BertForMaskedLM" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
3
null
--- license: apache-2.0 tags: - generated_from_trainer datasets: - clinc_oos metrics: - accuracy model-index: - name: distilbert-base-uncased-finetuned-clinc results: - task: name: Text Classification type: text-classification dataset: name: clinc_oos type: clinc_oos args: plus ...
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DiegoBalam12/institute_classification
[]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
null
--- tags: - CartPole-v1 - reinforce - reinforcement-learning - custom-implementation - deep-rl-class model-index: - name: Reinforce-3 results: - metrics: - type: mean_reward value: 471.20 +/- 86.40 name: mean_reward task: type: reinforcement-learning name: reinforcement-learning ...
[ -0.030025891959667206, 0.020807070657610893, 0.006371732801198959, 0.007786983158439398, 0.04292012006044388, -0.014740780927240849, -0.02912931516766548, -0.015446360222995281, -0.031221255660057068, 0.08450093120336533, 0.01915508322417736, -0.005576661787927151, 0.013422620482742786, 0....
DingleyMaillotUrgell/homer-bot
[ "pytorch", "gpt2", "text-generation", "en", "transformers", "conversational" ]
conversational
{ "architectures": [ "GPT2LMHeadModel" ], "model_type": "gpt2", "task_specific_params": { "conversational": { "max_length": 1000 }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
12
null
The review-annotation model is performing NER and able to annotate academic article review comments by identifying the four meaningful classes: - location - action - modal - trigger
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Dizoid/Lll
[]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
null
--- tags: - generated_from_trainer datasets: - samsum model-index: - name: pegasus-samsum results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # pegasus-samsum This ...
[ -0.03568824380636215, -0.010098084807395935, -0.009147671051323414, 0.03351537510752678, 0.04741881042718887, 0.020345380529761314, 0.001228302251547575, -0.01818520948290825, -0.04281949996948242, 0.06869734078645706, 0.03228101134300232, -0.015165985561907291, 0.012575543485581875, 0.035...
DoyyingFace/bert-asian-hate-tweets-concat-clean-with-unclean-valid
[ "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
--- license: apache-2.0 tags: - generated_from_trainer model-index: - name: distilroberta-base-finetuned-wikitextepoch_150 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...
[ -0.019858507439494133, -0.009072753600776196, -0.01084678340703249, 0.011549277231097221, 0.043809924274683, 0.01824745163321495, -0.015642356127500534, -0.01937520131468773, -0.04760860651731491, 0.057437095791101456, 0.025444386526942253, -0.03278879076242447, 0.004578865133225918, 0.039...
DoyyingFace/bert-asian-hate-tweets-concat-clean
[ "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
--- license: apache-2.0 tags: - generated_from_trainer model-index: - name: distilroberta-base-finetuned-marktextepoch_n200 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 com...
[ -0.011597119271755219, -0.0008132787770591676, -0.006062120199203491, 0.0039994497783482075, 0.0533616878092289, 0.01780041866004467, -0.012882650829851627, -0.01851995289325714, -0.04772764444351196, 0.05776441469788551, 0.024323852732777596, -0.04562543332576752, -0.0013105799444019794, ...
albert-base-v1
[ "pytorch", "tf", "safetensors", "albert", "fill-mask", "en", "dataset:bookcorpus", "dataset:wikipedia", "arxiv:1909.11942", "transformers", "exbert", "license:apache-2.0", "autotrain_compatible", "has_space" ]
fill-mask
{ "architectures": [ "AlbertForMaskedLM" ], "model_type": "albert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_...
38,156
2022-07-31T18:47:24Z
--- inference: false language: - "en" thumbnail: "https://drive.google.com/uc?export=view&id=1_n2kT6lBBs8C3rf8xfNURr_N2Ccx-A1S" tags: - text-to-image - dalle-mini license: "apache-2.0" datasets: - "succinctly/medium-titles-and-images" --- This is the [dalle-mini/dalle-mini](https://huggingface.co/dalle-mini/dalle-mi...
[ -0.00196053902618587, -0.028849860653281212, 0.011214233003556728, 0.06542612612247467, 0.0688951313495636, -0.004037502687424421, -0.010658103972673416, -0.01170110423117876, -0.00011512715718708932, 0.0416681133210659, 0.03915826603770256, -0.006620872300118208, -0.016302241012454033, 0....
albert-large-v1
[ "pytorch", "tf", "albert", "fill-mask", "en", "dataset:bookcorpus", "dataset:wikipedia", "arxiv:1909.11942", "transformers", "license:apache-2.0", "autotrain_compatible", "has_space" ]
fill-mask
{ "architectures": [ "AlbertForMaskedLM" ], "model_type": "albert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_...
687
2022-07-31T19:03:36Z
--- license: apache-2.0 tags: - generated_from_trainer metrics: - accuracy - recall - precision - f1 model-index: - name: distilbert-base-uncased_fine_tuned_body_text results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proo...
[ -0.008843565359711647, 0.005761060398072004, -0.028934214264154434, 0.031047439202666283, 0.049219273030757904, 0.015794822946190834, -0.032961469143629074, -0.04011552780866623, -0.04313960671424866, 0.06057143956422806, 0.028311144560575485, -0.02958018332719803, 0.02439926378428936, 0.0...
albert-xlarge-v1
[ "pytorch", "tf", "albert", "fill-mask", "en", "dataset:bookcorpus", "dataset:wikipedia", "arxiv:1909.11942", "transformers", "license:apache-2.0", "autotrain_compatible", "has_space" ]
fill-mask
{ "architectures": [ "AlbertForMaskedLM" ], "model_type": "albert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_...
341
2022-07-31T19:12:10Z
--- tags: - bert - mobilebert - oBERT language: en datasets: squad --- # mobilebert-uncased-finetuned-squadv1 This model is a finetuned version of the [mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased/tree/main) model on the SQuADv1 task. To make this TPU-trained model stable when used in PyTorch o...
[ -0.0015780155081301928, -0.006045085843652487, -0.0196243766695261, 0.05607636645436287, 0.01194574311375618, 0.025644691661000252, -0.0303594172000885, -0.012322871014475822, -0.032295335084199905, 0.04655197262763977, 0.036964088678359985, -0.007201489992439747, 0.014646661467850208, 0.0...
albert-xlarge-v2
[ "pytorch", "tf", "albert", "fill-mask", "en", "dataset:bookcorpus", "dataset:wikipedia", "arxiv:1909.11942", "transformers", "license:apache-2.0", "autotrain_compatible", "has_space" ]
fill-mask
{ "architectures": [ "AlbertForMaskedLM" ], "model_type": "albert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_...
2,973
2022-07-31T19:26:04Z
--- license: apache-2.0 tags: - generated_from_trainer datasets: - emotion metrics: - accuracy - f1 model-index: - name: distilbert-base-uncased-finetuned-emotion results: - task: name: Text Classification type: text-classification dataset: name: emotion type: emotion config: defau...
[ -0.01024161372333765, 0.010746883228421211, -0.029043875634670258, 0.03697516396641731, 0.06005765497684479, 0.033395830541849136, -0.023346057161688805, -0.036388006061315536, -0.0340706966817379, 0.056540150195360184, 0.018305066972970963, -0.0457451306283474, 0.03512263670563698, 0.0437...
albert-xxlarge-v2
[ "pytorch", "tf", "safetensors", "albert", "fill-mask", "en", "dataset:bookcorpus", "dataset:wikipedia", "arxiv:1909.11942", "transformers", "exbert", "license:apache-2.0", "autotrain_compatible", "has_space" ]
fill-mask
{ "architectures": [ "AlbertForMaskedLM" ], "model_type": "albert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_...
42,640
null
--- language: - rw library_name: nemo datasets: - mozilla-foundation/common_voice_9_0 thumbnail: null tags: - automatic-speech-recognition - speech - audio - Transducer - Conformer - Transformer - pytorch - NeMo - hf-asr-leaderboard license: cc-by-4.0 model-index: - name: stt_rw_conformer_transducer_large results: ...
[ -0.04249245300889015, -0.03456844761967659, -0.015153332613408566, 0.02507888339459896, 0.06586790084838867, 0.01838100329041481, -0.009957057423889637, -0.024099966511130333, -0.036746490746736526, 0.07381433248519897, 0.012822259217500687, -0.040808092802762985, -0.005119842942804098, 0....
bert-base-cased-finetuned-mrpc
[ "pytorch", "tf", "jax", "bert", "fill-mask", "transformers", "autotrain_compatible", "has_space" ]
fill-mask
{ "architectures": [ "BertForMaskedLM" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
11,644
2022-07-31T19:46:59Z
--- license: apache-2.0 tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: vit-base-patch32-384-finetuned-eurosat results: - task: name: Image Classification type: image-classification dataset: name: imagefolder type: imagefolder config:...
[ -0.016582146286964417, -0.016339702531695366, 0.003322298638522625, 0.02376643754541874, 0.03593847528100014, -0.010384447872638702, -0.006593220867216587, -0.0028373352251946926, -0.005612490698695183, 0.03902960941195488, 0.01934637501835823, -0.01185386348515749, 0.014852860942482948, 0...
bert-base-cased
[ "pytorch", "tf", "jax", "safetensors", "bert", "fill-mask", "en", "dataset:bookcorpus", "dataset:wikipedia", "arxiv:1810.04805", "transformers", "exbert", "license:apache-2.0", "autotrain_compatible", "has_space" ]
fill-mask
{ "architectures": [ "BertForMaskedLM" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
8,621,271
2022-07-31T20:00:07Z
--- "A bert model pretrained on earnings calls transcripts from SeekingAlpha.com"
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bert-base-german-cased
[ "pytorch", "tf", "jax", "safetensors", "bert", "fill-mask", "de", "transformers", "exbert", "license:mit", "autotrain_compatible", "has_space" ]
fill-mask
{ "architectures": [ "BertForMaskedLM" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
175,983
2022-07-31T20:57:24Z
--- license: apache-2.0 tags: - generated_from_trainer metrics: - f1 model-index: - name: distilbert-base-uncased_fold_1_binary results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this...
[ -0.02186601608991623, -0.0009444697061553597, -0.02135614864528179, 0.045914068818092346, 0.029397135600447655, 0.008464613929390907, -0.007376859430223703, -0.028780099004507065, -0.04263662174344063, 0.05471149832010269, 0.019069423899054527, -0.03934892266988754, 0.032667648047208786, 0...
bert-base-german-dbmdz-cased
[ "pytorch", "jax", "bert", "fill-mask", "de", "transformers", "license:mit", "autotrain_compatible", "has_space" ]
fill-mask
{ "architectures": [ "BertForMaskedLM" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
1,814
2022-07-31T20:57:40Z
--- library_name: keras --- ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Model Plot <details> <summary>View Model Plot</summary> ![Model Image](./model.png) </details>
[ -0.032183919101953506, -0.03589293733239174, 0.0042782919481396675, 0.01910523511469364, 0.02931181900203228, -0.0054577989503741264, -0.012205656617879868, -0.011269227601587772, -0.03940700367093086, 0.04582240432500839, 0.010003124363720417, -0.0066065918654203415, 0.025722190737724304, ...
bert-base-german-dbmdz-uncased
[ "pytorch", "jax", "safetensors", "bert", "fill-mask", "de", "transformers", "license:mit", "autotrain_compatible", "has_space" ]
fill-mask
{ "architectures": [ "BertForMaskedLM" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
68,305
2022-07-31T21:04:13Z
--- library_name: keras --- ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Model Plot <details> <summary>View Model Plot</summary> ![Model Image](./model.png) </details>
[ -0.032183919101953506, -0.03589293733239174, 0.0042782919481396675, 0.01910523511469364, 0.02931181900203228, -0.0054577989503741264, -0.012205656617879868, -0.011269227601587772, -0.03940700367093086, 0.04582240432500839, 0.010003124363720417, -0.0066065918654203415, 0.025722190737724304, ...
bert-base-multilingual-cased
[ "pytorch", "tf", "jax", "safetensors", "bert", "fill-mask", "multilingual", "af", "sq", "ar", "an", "hy", "ast", "az", "ba", "eu", "bar", "be", "bn", "inc", "bs", "br", "bg", "my", "ca", "ceb", "ce", "zh", "cv", "hr", "cs", "da", "nl", "en", "et", ...
fill-mask
{ "architectures": [ "BertForMaskedLM" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
4,749,504
2022-07-31T21:08:28Z
--- library_name: keras --- ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Model Plot <details> <summary>View Model Plot</summary> ![Model Image](./model.png) </details>
[ -0.032183919101953506, -0.03589293733239174, 0.0042782919481396675, 0.01910523511469364, 0.02931181900203228, -0.0054577989503741264, -0.012205656617879868, -0.011269227601587772, -0.03940700367093086, 0.04582240432500839, 0.010003124363720417, -0.0066065918654203415, 0.025722190737724304, ...
bert-base-uncased
[ "pytorch", "tf", "jax", "rust", "safetensors", "bert", "fill-mask", "en", "dataset:bookcorpus", "dataset:wikipedia", "arxiv:1810.04805", "transformers", "exbert", "license:apache-2.0", "autotrain_compatible", "has_space" ]
fill-mask
{ "architectures": [ "BertForMaskedLM" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
59,663,489
2022-07-31T21:33:10Z
--- license: apache-2.0 tags: - generated_from_trainer metrics: - f1 model-index: - name: distilbert-base-uncased_fold_2_binary results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this...
[ -0.021265413612127304, -0.002794839907437563, -0.01894095540046692, 0.04683630168437958, 0.02963586151599884, 0.008229591883718967, -0.007200202438980341, -0.027953678742051125, -0.04030250385403633, 0.053638022392988205, 0.020035739988088608, -0.03550396487116814, 0.031942009925842285, 0....
bert-large-uncased-whole-word-masking
[ "pytorch", "tf", "jax", "safetensors", "bert", "fill-mask", "en", "dataset:bookcorpus", "dataset:wikipedia", "arxiv:1810.04805", "transformers", "license:apache-2.0", "autotrain_compatible", "has_space" ]
fill-mask
{ "architectures": [ "BertForMaskedLM" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
76,685
2022-07-31T21:54:02Z
--- license: apache-2.0 tags: - generated_from_trainer metrics: - f1 model-index: - name: distilbert-base-uncased_fold_4_binary results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this...
[ -0.024940380826592445, -0.00004101218655705452, -0.021052183583378792, 0.04399188607931137, 0.02850298024713993, 0.00993390567600727, -0.0072809383273124695, -0.029681866988539696, -0.043114952743053436, 0.05430801957845688, 0.016713816672563553, -0.040073640644550323, 0.034665726125240326, ...
bert-large-uncased
[ "pytorch", "tf", "jax", "safetensors", "bert", "fill-mask", "en", "dataset:bookcorpus", "dataset:wikipedia", "arxiv:1810.04805", "transformers", "license:apache-2.0", "autotrain_compatible", "has_space" ]
fill-mask
{ "architectures": [ "BertForMaskedLM" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
1,058,496
2022-07-31T22:04:19Z
--- license: apache-2.0 tags: - generated_from_trainer metrics: - f1 model-index: - name: distilbert-base-uncased_fold_5_binary results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this...
[ -0.021077601239085197, -0.0010046068346127868, -0.01923852227628231, 0.042408812791109085, 0.031242074444890022, 0.007344964426010847, -0.009213345125317574, -0.0293628741055727, -0.04220617562532425, 0.0533171221613884, 0.02126261033117771, -0.038731154054403305, 0.029931029304862022, 0.0...
camembert-base
[ "pytorch", "tf", "safetensors", "camembert", "fill-mask", "fr", "dataset:oscar", "arxiv:1911.03894", "transformers", "license:mit", "autotrain_compatible", "has_space" ]
fill-mask
{ "architectures": [ "CamembertForMaskedLM" ], "model_type": "camembert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_...
1,440,898
null
--- license: apache-2.0 tags: - generated_from_trainer metrics: - f1 model-index: - name: distilbert-base-uncased_fold_6_binary results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this...
[ -0.024077750742435455, -0.0018004854209721088, -0.017253510653972626, 0.04481394216418266, 0.031127721071243286, 0.005016089417040348, -0.006348941009491682, -0.030494652688503265, -0.04330442473292351, 0.05159839242696762, 0.01719079352915287, -0.04202468320727348, 0.031935133039951324, 0...
distilbert-base-german-cased
[ "pytorch", "safetensors", "distilbert", "fill-mask", "de", "transformers", "license:apache-2.0", "autotrain_compatible", "has_space" ]
fill-mask
{ "architectures": [ "DistilBertForMaskedLM" ], "model_type": "distilbert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repea...
43,667
2022-07-31T22:26:16Z
--- license: mit tags: - generated_from_trainer metrics: - f1 model-index: - name: xlnet-base-cased_fold_1_binary 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. --> ...
[ -0.035063743591308594, -0.0024289144203066826, -0.005910505075007677, 0.03876244276762009, 0.006968713365495205, 0.005935218650847673, -0.008350635878741741, -0.015587669797241688, -0.035542819648981094, 0.047498855739831924, 0.006096379831433296, -0.03888076916337013, 0.04180769994854927, ...
distilgpt2
[ "pytorch", "tf", "jax", "tflite", "rust", "coreml", "safetensors", "gpt2", "text-generation", "en", "dataset:openwebtext", "arxiv:1910.01108", "arxiv:2201.08542", "arxiv:2203.12574", "arxiv:1910.09700", "arxiv:1503.02531", "transformers", "exbert", "license:apache-2.0", "model-...
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...
1,611,668
2022-07-31T23:17:27Z
--- license: mit --- ### marian-mt-en-pcm * source language: en (English) * target language: pcm (Nigerian Pidgin) * dataset: Parallel Sentences from the message translation (English) and Pidgin translation of the Bible. * model: transformer-align * pre-processing: normalization + SentencePiece ## Performance | t...
[ -0.02751731313765049, -0.027471590787172318, -0.02075587399303913, 0.036402080208063126, 0.049564141780138016, 0.03413178771734238, 0.001046680728904903, -0.006640219129621983, -0.044707801192998886, 0.04079176485538483, 0.03198949620127678, 0.004287503194063902, 0.0295103807002306, 0.0489...
13306330378/huiqi_model
[]
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
2022-08-01T09:05:27Z
--- license: apache-2.0 tags: - generated_from_trainer datasets: - wikiann model-index: - name: ner_hindi_bert 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. --> # ...
[ -0.008495458401739597, -0.011777816340327263, -0.025036131963133812, 0.05249506235122681, 0.008824394084513187, 0.03135323151946068, -0.008258670568466187, -0.035154182463884354, -0.040185097604990005, 0.06267492473125458, 0.005688438657671213, -0.032077059149742126, 0.026045426726341248, ...
Ab2021/bookst5
[]
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: wav2vec2-large-xlsr-korean-demo-with-LM 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. --...
[ -0.032972682267427444, -0.002074599964544177, -0.006903385277837515, 0.030595343559980392, 0.039078034460544586, 0.003769249189645052, -0.002781975083053112, -0.006298068445175886, -0.029023660346865654, 0.05055352672934532, 0.026029126718640327, -0.03467169776558876, -0.0020319302566349506,...
AdapterHub/bert-base-uncased-pf-emotion
[ "bert", "en", "dataset:emotion", "arxiv:2104.08247", "adapter-transformers", "text-classification" ]
text-classification
{ "architectures": null, "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": null, "num_bea...
165
null
--- license: apache-2.0 tags: - generated_from_trainer datasets: - squad_v2_yash model-index: - name: distilbert-base-cased-distilled-squad-finetuned-squad results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and c...
[ -0.02334451675415039, -0.010466476902365685, -0.029872843995690346, 0.04399558901786804, 0.06588822603225708, 0.013638913631439209, -0.03252403438091278, -0.0020300373435020447, -0.02704586088657379, 0.047150637954473495, 0.041449174284935, -0.009344367310404778, 0.015150382183492184, 0.04...
AdapterHub/bert-base-uncased-pf-ud_pos
[ "bert", "en", "dataset:universal_dependencies", "arxiv:2104.08247", "adapter-transformers", "token-classification", "adapterhub:pos/ud_ewt" ]
token-classification
{ "architectures": null, "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": null, "num_bea...
1
null
--- license: "cc-by-nc-4.0" tags: - vision - video-classification --- # VideoMAE (large-sized model, pre-trained only) VideoMAE model pre-trained on Kinetics-400 for 1600 epochs in a self-supervised way. It was introduced in the paper [VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Vid...
[ -0.05034109577536583, -0.006446405779570341, 0.016595983877778053, 0.017321454361081123, 0.05555291101336479, 0.008580776862800121, -0.017150914296507835, -0.01761246658861637, -0.012368252500891685, 0.058586351573467255, 0.021652817726135254, 0.0010374943958595395, 0.0016604856355115771, ...
AimB/konlpy_berttokenizer_helsinki
[]
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 metrics: - accuracy - f1 model-index: - name: chinese-roberta-wwm-ext-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 remo...
[ -0.03414881229400635, -0.008228074759244919, 0.009024746716022491, 0.033780597150325775, 0.03380609676241875, 0.024467259645462036, -0.020888259634375572, -0.017616184428334236, -0.02503734454512596, 0.045192841440439224, 0.020215662196278572, -0.021782614290714264, 0.017903616651892662, 0...
AimB/mT5-en-kr-aihub-netflix
[]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
null
--- library_name: stable-baselines3 tags: - SpaceInvadersNoFrameskip-v4 - deep-reinforcement-learning - reinforcement-learning - stable-baselines3 model-index: - name: DQN results: - metrics: - type: mean_reward value: 603.00 +/- 194.90 name: mean_reward task: type: reinforcement-learning ...
[ -0.039643194526433945, -0.015204126946628094, -0.01696636714041233, 0.03678873926401138, 0.05006539076566696, -0.003916533663868904, -0.012689989991486073, -0.02512257546186447, -0.03498508036136627, 0.05258940905332565, 0.020892975851893425, -0.03308204934000969, 0.018954439088702202, 0.0...
Akash7897/distilbert-base-uncased-finetuned-cola
[ "pytorch", "tensorboard", "distilbert", "text-classification", "dataset:glue", "transformers", "generated_from_trainer", "license:apache-2.0", "model-index" ]
text-classification
{ "architectures": [ "DistilBertForSequenceClassification" ], "model_type": "distilbert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, ...
31
null
--- license: "cc-by-nc-4.0" tags: - vision - video-classification --- # VideoMAE (base-sized model, pre-trained only) VideoMAE model pre-trained on Kinetics-400 for 1600 epochs in a self-supervised way. It was introduced in the paper [VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Vide...
[ -0.05032359063625336, -0.006805129814893007, 0.016559842973947525, 0.0176254790276289, 0.05500936135649681, 0.009632646106183529, -0.017321690917015076, -0.016665341332554817, -0.013045869767665863, 0.058868635445833206, 0.021125003695487976, 0.0009768666932359338, 0.0008586115436628461, 0...
Akashpb13/xlsr_kurmanji_kurdish
[ "pytorch", "safetensors", "wav2vec2", "automatic-speech-recognition", "kmr", "ku", "dataset:mozilla-foundation/common_voice_8_0", "transformers", "mozilla-foundation/common_voice_8_0", "generated_from_trainer", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard", "license:apache-...
automatic-speech-recognition
{ "architectures": [ "Wav2Vec2ForCTC" ], "model_type": "wav2vec2", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_s...
10
null
--- tags: - fastai --- # Amazing! 🥳 Congratulations on hosting your fastai model on the Hugging Face Hub! # Some next steps 1. Fill out this model card with more information (see the template below and the [documentation here](https://huggingface.co/docs/hub/model-repos))! 2. Create a demo in Gradio or Streamlit u...
[ -0.021706635132431984, -0.033120911568403244, 0.0069284033961594105, 0.022917678579688072, 0.010587208904325962, 0.024608587846159935, -0.02954155206680298, -0.016725419089198112, -0.028829533606767654, 0.032675109803676605, 0.03176262229681015, 0.010438955388963223, 0.04351669177412987, 0...
Akashpb13/xlsr_maltese_wav2vec2
[ "pytorch", "jax", "wav2vec2", "automatic-speech-recognition", "mt", "dataset:common_voice", "transformers", "audio", "speech", "xlsr-fine-tuning-week", "license:apache-2.0", "model-index" ]
automatic-speech-recognition
{ "architectures": [ "Wav2Vec2ForCTC" ], "model_type": "wav2vec2", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_s...
8
null
--- tags: - translation license: apache-2.0 --- ### opus-mt-fr-en * source languages: fr * target languages: en * OPUS readme: [fr-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/fr-en/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * downl...
[ -0.01217317022383213, -0.029958954080939293, -0.020741451531648636, 0.039299946278333664, 0.0310744047164917, 0.02110043168067932, -0.0036430442705750465, -0.010182644240558147, -0.05257464945316315, 0.06225619465112686, 0.010473795235157013, -0.013695181347429752, -0.0005088504985906184, ...
Akira-Yana/distilbert-base-uncased-finetuned-cola
[]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
null
--- license: apache-2.0 tags: - generated_from_trainer metrics: - f1 model-index: - name: distilbert-base-uncased_fold_8_binary_v1 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove t...
[ -0.022930067032575607, -0.0013733264058828354, -0.019114285707473755, 0.044528309255838394, 0.03021739237010479, 0.0076247453689575195, -0.0045363097451627254, -0.030295560136437416, -0.03899340704083443, 0.05399002879858017, 0.017582714557647705, -0.03835950791835785, 0.036352939903736115, ...
Akiva/Joke
[]
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 metrics: - f1 model-index: - name: distilbert-base-uncased_fold_9_binary_v1 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove t...
[ -0.015934757888317108, -0.0020808374974876642, -0.021600207313895226, 0.04988674074411392, 0.029230477288365364, 0.0075054047629237175, -0.01174428965896368, -0.0254824161529541, -0.039735302329063416, 0.050765469670295715, 0.016065681353211403, -0.03804748132824898, 0.03394288197159767, 0...
Akjder/DialoGPT-small-harrypotter
[ "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...
8
null
--- annotations_creators: [] language: - ro language_creators: - machine-generated license: - apache-2.0 multilinguality: - monolingual pretty_name: BlackKakapo/t5-small-paraphrase-ro size_categories: - 10K<n<100K source_datasets: - original tags: [] task_categories: - text2text-generation task_ids: [] --- # Romanian ...
[ -0.0017503377748653293, -0.0561387874186039, -0.018588468432426453, 0.039829909801483154, 0.05020064860582352, 0.03604207932949066, -0.006731451954692602, -0.0014635624829679728, -0.04881779104471207, 0.0771956667304039, 0.024705860763788223, -0.007902780547738075, 0.0008128051995299757, 0...
Aklily/Lilys
[]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
null
--- license: apache-2.0 tags: - generated_from_trainer datasets: - imdb model-index: - name: distilbert-base-uncased-finetuned-imdb results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove ...
[ -0.016133679077029228, 0.0064472598023712635, -0.03361671417951584, 0.04632376879453659, 0.04643043503165245, 0.02636859379708767, -0.01986122503876686, -0.026042833924293518, -0.030373787507414818, 0.06582445651292801, 0.04666623845696449, -0.025120461359620094, 0.013900191523134708, 0.04...
AkshatSurolia/BEiT-FaceMask-Finetuned
[ "pytorch", "beit", "image-classification", "dataset:Face-Mask18K", "transformers", "license:apache-2.0", "autotrain_compatible" ]
image-classification
{ "architectures": [ "BeitForImageClassification" ], "model_type": "beit", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat...
239
null
--- language: - ru tags: - PyTorch - OCR - Segmentation - HTR datasets: - "sberbank-ai/school_notebooks_RU" - "sberbank-ai/school_notebooks_EN" license: mit --- This is a weights storage for models trained by [ReadingPipeline](https://github.com/ai-forever/ReadingPipeline) The weights are for ocr and segmentations mo...
[ -0.02853146754205227, -0.04535922035574913, -0.01314342487603426, 0.039018359035253525, 0.024004338309168816, 0.004515372682362795, -0.017145588994026184, 0.0022397912107408047, -0.08058828115463257, 0.07268940657377243, 0.03783123567700386, 0.0226557869464159, 0.01850593276321888, 0.03930...
AkshatSurolia/ConvNeXt-FaceMask-Finetuned
[ "pytorch", "safetensors", "convnext", "image-classification", "dataset:Face-Mask18K", "transformers", "license:apache-2.0", "autotrain_compatible", "has_space" ]
image-classification
{ "architectures": [ "ConvNextForImageClassification" ], "model_type": "convnext", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "n...
56
null
--- license: apache-2.0 tags: - generated_from_trainer metrics: - f1 model-index: - name: distilbert-base-uncased_fold_10_binary_v1 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove ...
[ -0.022236986085772514, -0.000023870752556831576, -0.015940336510539055, 0.04586305841803551, 0.027165651321411133, 0.01062797661870718, -0.007121596485376358, -0.024347757920622826, -0.04167050123214722, 0.053650304675102234, 0.02120068669319153, -0.039778999984264374, 0.03329240158200264, ...
AlanDev/test
[]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
null
git lfs install git clone https://huggingface.co/Saraswati/ppo-CartPole-v2
[ -0.016497407108545303, -0.005955989938229322, 0.0036931976210325956, 0.0005342770600691438, 0.021226707845926285, 0.0005977900000289083, 0.02540159784257412, 0.02471158467233181, -0.025982219725847244, 0.043336596339941025, -0.0009734156774356961, -0.004444624297320843, 0.04614739120006561, ...
AlbertHSU/ChineseFoodBert
[ "pytorch", "bert", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "BertModel" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": nul...
15
null
--- language: - hr library_name: nemo datasets: - ParlaSpeech-HR-v1.0 thumbnail: null tags: - automatic-speech-recognition - speech - audio - Transducer - Conformer - Transformer - pytorch - NeMo - hf-asr-leaderboard license: cc-by-4.0 --- # NVIDIA Conformer-Transducer Large (Croatian) <style> img { display: inline;...
[ -0.029142171144485474, -0.03428839147090912, -0.0040444922633469105, 0.029889969155192375, 0.05904928594827652, 0.010715572163462639, -0.013938238844275475, -0.012688257731497288, -0.043985165655612946, 0.06665799766778946, 0.013361737132072449, -0.02858489565551281, 0.0027770553715527058, ...
Alberto15Romero/GptNeo
[]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
null
--- tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: categorization-finetuned-20220721-164940-pruned-20220803-123018 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it,...
[ -0.026312923058867455, 0.003562570083886385, 0.003709779353812337, 0.035825714468955994, 0.036183033138513565, 0.006639120168983936, -0.012170210480690002, -0.004465078003704548, -0.03662475571036339, 0.05656060576438904, 0.017469467595219612, -0.021313410252332687, 0.02623445726931095, 0....
AlchemistDude/DialoGPT-medium-Gon
[]
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 metrics: - f1 model-index: - name: distilbert-base-uncased_fold_13_binary_v1 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove ...
[ -0.02024339698255062, -0.005055587738752365, -0.022732436656951904, 0.04583212733268738, 0.031878527253866196, 0.00833153072744608, -0.008338809944689274, -0.029378481209278107, -0.03691086545586586, 0.05086590722203255, 0.019442565739154816, -0.038351837545633316, 0.02822829969227314, 0.0...
Aleksandar/distilbert-srb-ner-setimes
[ "pytorch", "distilbert", "token-classification", "transformers", "generated_from_trainer", "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: zh widget: - text: "江苏警方通报特斯拉冲进店铺" --- # Chinese RoBERTa-Base Model for NER ## Model description The model is used for named entity recognition. You can download the model either from the [UER-py Modelzoo page](https://github.com/dbiir/UER-py/wiki/Modelzoo) (in UER-py format), or via HuggingFace from...
[ -0.04656200855970383, -0.0163695327937603, 0.01349230483174324, 0.04242786020040512, 0.03409507870674133, 0.02240309864282608, -0.03368116170167923, -0.042005378752946854, -0.049095865339040756, 0.05286697298288345, 0.020870409905910492, -0.0036012455821037292, 0.005991415120661259, 0.0421...
Alicanke/Wyau
[]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
null
--- tags: - autotrain - text-classification language: - en widget: - text: "I love AutoTrain 🤗" datasets: - BenWord/autotrain-data-APMv2Multiclass co2_eq_emissions: emissions: 2.4364900803769225 --- # Model Trained Using AutoTrain - Problem type: Multi-class Classification - Model ID: 1216046004 - CO2 Emissions (i...
[ -0.02454012632369995, -0.023676862940192223, -0.012089306488633156, 0.03579743951559067, 0.03249967843294144, 0.03997073322534561, -0.025828693062067032, -0.021714048460125923, -0.036694470793008804, 0.08080027252435684, 0.015398896299302578, 0.029020115733146667, -0.0021714584436267614, 0...
Alifarsi/t5-small-finetuned-xsum
[]
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: Bio_ClinicalBERT_fold_3_binary_v1 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -...
[ -0.028048736974596977, -0.026311838999390602, 0.0005194596596993506, 0.021559925749897957, 0.002303146757185459, 0.009629159234464169, -0.015520052053034306, -0.024860676378011703, -0.027071217074990273, 0.04414697736501694, 0.02278555929660797, -0.03483370691537857, 0.03711814433336258, 0...
Alireza1044/albert-base-v2-cola
[ "pytorch", "tensorboard", "albert", "text-classification", "en", "dataset:glue", "transformers", "generated_from_trainer", "license:apache-2.0" ]
text-classification
{ "architectures": [ "AlbertForSequenceClassification" ], "model_type": "albert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no...
32
null
--- license: mit tags: - generated_from_trainer metrics: - f1 model-index: - name: Bio_ClinicalBERT_fold_4_binary_v1 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -...
[ -0.029988178983330727, -0.020734136924147606, 0.004216321278363466, 0.022769344970583916, -0.0016477766912430525, 0.00814609695225954, -0.014274661429226398, -0.024786433205008507, -0.028232576325535774, 0.041415583342313766, 0.01839389093220234, -0.03693650662899017, 0.04566216841340065, ...
Allybaby21/Allysai
[]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
null
--- tags: - generated_from_keras_callback model-index: - name: mal_tls-bert-base-relu-w1q8 results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # mal_tls-bert-base-relu-w1q...
[ -0.03471420332789421, -0.016437865793704987, -0.014542641118168831, 0.028444943949580193, 0.03812654688954353, 0.030728427693247795, -0.010702874511480331, -0.015498079359531403, -0.003960095811635256, 0.03499295189976692, 0.014571980573236942, -0.03236846998333931, 0.009195615537464619, 0...
Alvenir/wav2vec2-base-da
[ "pytorch", "wav2vec2", "pretraining", "da", "transformers", "speech", "license:apache-2.0" ]
null
{ "architectures": [ "Wav2Vec2ForPreTraining" ], "model_type": "wav2vec2", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat...
62
null
--- license: apache-2.0 tags: - generated_from_trainer model-index: - name: output 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. --> # output This model is a fine...
[ -0.039195090532302856, 0.00026076938956975937, -0.013765871524810791, 0.03539039567112923, 0.04129885137081146, 0.015521452762186527, -0.011543446220457554, -0.009524853900074959, -0.02416379749774933, 0.05849277228116989, 0.029214931651949883, -0.036075517535209656, 0.006822895724326372, ...
AmitT/test
[]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
null
--- language: 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...
[ 0.008167670108377934, -0.03683605417609215, 0.0032514259219169617, 0.03748267516493797, 0.04343951493501663, 0.013037579134106636, -0.02626718021929264, -0.002626602305099368, -0.03466589003801346, 0.040421705693006516, -0.007879853248596191, -0.012293575331568718, 0.005903864745050669, 0....
Amitabh/doc-classification
[]
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: protBERTbfd_AAV2_regressor 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. --> # protBERTbfd_AAV2_regressor ...
[ -0.026428937911987305, -0.014853253960609436, -0.012580865062773228, 0.04201203212141991, 0.022458836436271667, 0.013726289384067059, -0.020997541025280952, -0.034693632274866104, -0.043340880423784256, 0.033698540180921555, 0.005108064506202936, -0.015082175843417645, -0.004518609028309584,...
AnonymousSub/AR_rule_based_roberta_only_classfn_twostage_epochs_1_shard_10
[ "pytorch", "roberta", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "RobertaModel" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
6
null
--- license: apache-2.0 tags: - generated_from_keras_callback model-index: - name: silviacamplani/distilbert-base-uncased-finetuned-dapt-ner-ai_data results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, t...
[ -0.04116884618997574, -0.003230869071558118, -0.005299677606672049, 0.03590177372097969, 0.04224633052945137, 0.020355645567178726, -0.02524893917143345, -0.019307930022478104, -0.05295965448021889, 0.059501104056835175, 0.030536159873008728, -0.022195762023329735, 0.019779225811362267, 0....
AnonymousSub/SR_rule_based_roberta_bert_quadruplet_epochs_1_shard_10
[ "pytorch", "roberta", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "RobertaModel" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
2
null
--- tags: - generated_from_trainer model-index: - name: article_title 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. --> # article_title This model is a fine-tuned...
[ -0.043117206543684006, -0.017837366089224815, -0.013071774505078793, 0.053740546107292175, 0.04749489575624466, 0.017282063141465187, 0.0017696944996714592, -0.01876983791589737, -0.03037072718143463, 0.05365026742219925, 0.03142567351460457, 0.0021409126929938793, 0.007373012602329254, 0....
AnonymousSub/SR_rule_based_roberta_bert_triplet_epochs_1_shard_1
[ "pytorch", "roberta", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "RobertaModel" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
2
null
--- datasets: - relbert/conceptnet_high_confidence model-index: - name: relbert/roberta-large-conceptnet-mask-prompt-b-nce results: - task: name: Relation Mapping type: sorting-task dataset: name: Relation Mapping args: relbert/relation_mapping type: relation-mapping metrics: ...
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AnonymousSub/SR_rule_based_roberta_twostage_quadruplet_epochs_1_shard_10
[ "pytorch", "roberta", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "RobertaModel" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
8
null
--- tags: - generated_from_trainer model-index: - name: DNADebertaSentencepiece30k_continuation_continuation 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. --> # DN...
[ -0.022119369357824326, -0.0325690433382988, -0.008139492943882942, 0.041245609521865845, 0.027388012036681175, 0.007029158994555473, 0.0033327327109873295, -0.031108267605304718, -0.05729023367166519, 0.06470675766468048, 0.012564311735332012, -0.02868964523077011, 0.007574996445327997, 0....
AnonymousSub/SR_rule_based_roberta_twostagequadruplet_hier_epochs_1_shard_1
[ "pytorch", "roberta", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "RobertaModel" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
4
null
--- tags: - generated_from_trainer model-index: - name: DNADebertaSentencepiece10k_continuation_continuation 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. --> # DN...
[ -0.019139982759952545, -0.028274377807974815, -0.004087674431502819, 0.04000668600201607, 0.02566266804933548, 0.010489127598702908, 0.0029744517523795366, -0.029480021446943283, -0.05904015153646469, 0.06584873795509338, 0.014006848447024822, -0.027631716802716255, 0.007224603556096554, 0...
AnonymousSub/SR_rule_based_roberta_twostagequadruplet_hier_epochs_1_shard_10
[ "pytorch", "roberta", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "RobertaModel" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
4
null
--- license: apache-2.0 tags: - generated_from_keras_callback model-index: - name: cochonaki/distilbert-base-uncased-finetuned-cola results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this c...
[ -0.03300632908940315, 0.004344874061644077, -0.007977842353284359, 0.029910536482930183, 0.03798200935125351, 0.006399502977728844, -0.030535219237208366, -0.014493372291326523, -0.04689745232462883, 0.053136661648750305, 0.04551185294985771, -0.01127086766064167, 0.02574954740703106, 0.03...
AnonymousSub/SR_rule_based_roberta_twostagetriplet_epochs_1_shard_1
[ "pytorch", "roberta", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "RobertaModel" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
8
null
--- language: en tags: [Ad-Corre, facial expression recognition, emotion recognition, expression recognition, computer vision, CNN, loss, IEEE Access, Tensor Flow ] thumbnail: license: mit --- # Ad-Corre Ad-Corre: Adaptive Correlation-Based Loss for Facial Expression Recognition in the Wild [![PWC](https://img.s...
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AnonymousSub/SR_rule_based_roberta_twostagetriplet_epochs_1_shard_10
[ "pytorch", "roberta", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "RobertaModel" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
4
null
--- language: en tags: [cvpr2021, computer vision, face alignment, facial landmark point, pose estimation, face pose tracking, CNN, loss, custom loss, ASMNet, Tensor Flow] license: mit --- [![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/deep-active-shape-model-for-face-alignment/pose...
[ -0.023668840527534485, -0.01780795492231846, 0.010502769611775875, 0.031630806624889374, 0.03174590691924095, 0.0006808798643760383, -0.01607391983270645, 0.01595894806087017, -0.015347137115895748, 0.05645092949271202, 0.015177689492702484, -0.0023079595994204283, 0.030807076022028923, 0....
AnonymousSub/SR_rule_based_roberta_twostagetriplet_hier_epochs_1_shard_1
[ "pytorch", "roberta", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "RobertaModel" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
4
null
--- language: en tags: [ computer vision, face alignment, facial landmark point, CNN, Knowledge Distillation, loss, CVIU, Tensor Flow] thumbnail: license: mit --- [![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/facial-landmark-points-detection-using/face-alignment-on-cofw)](https:/...
[ -0.017576301470398903, -0.014497203752398491, 0.0019404981285333633, 0.012416323646903038, 0.022221365943551064, 0.0017180192517116666, -0.003912483341991901, 0.005751853808760643, -0.024074619635939598, 0.06871352344751358, 0.03661634773015976, 0.0080170389264822, 0.01675686240196228, 0.0...
AnonymousSub/SR_rule_based_twostage_quadruplet_epochs_1_shard_1
[ "pytorch", "bert", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "BertModel" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": nul...
3
null
--- license: apache-2.0 tags: - generated_from_trainer datasets: - wikigold_splits metrics: - precision - recall - f1 - accuracy model-index: - name: wikigold_trained_no_DA_testing2 results: - task: name: Token Classification type: token-classification dataset: name: wikigold_splits type...
[ -0.029574451968073845, -0.027202971279621124, -0.018861131742596626, 0.012208712287247181, 0.025625139474868774, 0.017354590818285942, -0.01492098718881607, -0.02133364789187908, -0.04309479147195816, 0.048633038997650146, 0.023610590025782585, 0.00409715436398983, -0.010812398977577686, 0...
AnonymousSub/SR_rule_based_twostagetriplet_hier_epochs_1_shard_1
[ "pytorch", "bert", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "BertModel" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": nul...
2
null
--- tags: - generated_from_trainer model-index: - name: article_title_2299 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. --> # article_title_2299 This model is a ...
[ -0.040815018117427826, -0.01715877093374729, -0.011996765621006489, 0.05481957271695137, 0.049261510372161865, 0.013364337384700775, 0.00015129795065149665, -0.019373441115021706, -0.03007400594651699, 0.053408145904541016, 0.034436337649822235, 0.0036395371425896883, 0.004669895861297846, ...
AnonymousSub/cline-emanuals-techqa
[ "pytorch", "roberta", "question-answering", "transformers", "autotrain_compatible" ]
question-answering
{ "architectures": [ "RobertaForQuestionAnswering" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_re...
4
2022-08-04T20:36:37Z
--- tags: - generated_from_trainer datasets: - common_voice model-index: - name: facebook_large_CV_bn3 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. --> # facebook...
[ -0.0331936739385128, -0.0028062197379767895, -0.015766378492116928, 0.039460618048906326, 0.03236546739935875, 0.015781700611114502, -0.019391022622585297, -0.018317651003599167, -0.01621118001639843, 0.04784770682454109, 0.04774334281682968, -0.01319076307117939, 0.012378963641822338, 0.0...
AnonymousSub/cline-papers-biomed-0.618
[ "pytorch", "roberta", "transformers" ]
null
{ "architectures": [ "LecbertForPreTraining" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_n...
2
2022-08-04T21:06:12Z
--- tags: - generated_from_trainer model-index: - name: multi_news_article_title_2299 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. --> # multi_news_article_title_...
[ -0.047456491738557816, -0.03424398973584175, -0.01963910274207592, 0.04960166662931442, 0.05594291165471077, 0.026002246886491776, 0.008014393039047718, -0.03749777004122734, -0.02236088737845421, 0.04654552787542343, 0.03432394191622734, 0.003384837880730629, 0.010518084280192852, 0.04462...
AnonymousSub/cline-papers-roberta-0.585
[ "pytorch", "roberta", "transformers" ]
null
{ "architectures": [ "LecbertForPreTraining" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_n...
1
2022-08-04T21:31:59Z
--- tags: - generated_from_keras_callback model-index: - name: mal-tls-bert-large-relu-w8a8 results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # mal-tls-bert-large-relu-w...
[ -0.029083067551255226, -0.008668017573654652, -0.009057994931936264, 0.03090425208210945, 0.04481402039527893, 0.02264278009533882, -0.015184330753982067, -0.02520555816590786, 0.00431651109829545, 0.03638361021876335, 0.013215027749538422, -0.028021549805998802, 0.012166273780167103, 0.04...
AnonymousSub/consert-s10-SR
[ "pytorch", "bert", "text-classification", "transformers" ]
text-classification
{ "architectures": [ "BertForSequenceClassification" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_rep...
28
2022-08-04T22:50:01Z
--- license: apache-2.0 tags: - generated_from_trainer metrics: - f1 - accuracy - precision - recall model-index: - name: soft-search results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remov...
[ -0.015069582499563694, 0.014252660796046257, -0.011111375875771046, 0.03294840827584267, 0.022053103893995285, 0.021734250709414482, -0.022766079753637314, -0.006437710486352444, -0.04727407544851303, 0.06472234427928925, 0.011812680400907993, -0.03494475036859512, 0.028062378987669945, 0....
AnonymousSub/roberta-base_wikiqa
[ "pytorch", "roberta", "text-classification", "transformers" ]
text-classification
{ "architectures": [ "RobertaForSequenceClassification" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "...
25
2022-08-05T04:33:44Z
--- license: mit tags: - generated_from_trainer model-index: - name: Bio_ClinicalBERT-zero-shot-finetuned-all-cad 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. --> ...
[ -0.01476236805319786, -0.009196123108267784, -0.0060783266089856625, 0.005269201472401619, 0.02478831447660923, 0.023023871704936028, -0.02049720101058483, -0.028486959636211395, -0.034360360354185104, 0.047154419124126434, 0.023786241188645363, -0.01648956537246704, 0.04141726717352867, 0...
AnonymousSub/rule_based_bert_quadruplet_epochs_1_shard_10
[ "pytorch", "bert", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "BertModel" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": nul...
8
2022-08-05T05:12:27Z
--- license: mit tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: Bio_ClinicalBERT-zero-shot-finetuned-50cad-50noncad-optimal results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and com...
[ -0.014904695563018322, -0.006020913831889629, -0.002197636291384697, 0.009150275029242039, 0.02770993299782276, 0.015530520118772984, -0.02381700463593006, -0.025152236223220825, -0.03634290397167206, 0.0474543459713459, 0.025059588253498077, -0.0222095288336277, 0.030085429549217224, 0.06...
AnonymousSub/rule_based_hier_quadruplet_epochs_1_shard_10
[ "pytorch", "bert", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "BertModel" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": nul...
4
null
--- tags: - unity-ml-agents - ml-agents - deep-reinforcement-learning - reinforcement-learning - ML-Agents-Pyramids library_name: ml-agents --- # **ppo** Agent playing **Pyramids** This is a trained model of a **ppo** agent playing **Pyramids** using the [Unity ML-Age...
[ -0.053315646946430206, 0.005693919025361538, -0.00565043231472373, 0.058035578578710556, 0.026999980211257935, 0.028895262628793716, -0.003123675240203738, -0.03060598485171795, -0.006225902587175369, 0.050742074847221375, 0.018456103280186653, -0.011628294363617897, 0.0070838299579918385, ...
AnonymousSub/rule_based_only_classfn_epochs_1_shard_10
[ "pytorch", "bert", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "BertModel" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": nul...
7
null
--- license: apache-2.0 tags: - generated_from_trainer model-index: - name: Spoof_detection 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. --> # Spoof_detection Th...
[ -0.03575614467263222, -0.010085317306220531, -0.015335637144744396, 0.01924852840602398, 0.04123823344707489, 0.020765205845236778, -0.005461511667817831, -0.004785171244293451, -0.03159693256020546, 0.055089566856622696, 0.014388212002813816, -0.012699001468718052, -0.004106464330106974, ...
AnonymousSub/rule_based_roberta_only_classfn_epochs_1_shard_1
[ "pytorch", "roberta", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "RobertaModel" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
7
null
--- license: apache-2.0 tags: - generated_from_trainer datasets: - fairytale_qa metrics: - rouge model-index: - name: t5-base-QG-finetuned-FairytaleQA results: - task: name: Sequence-to-sequence Language Modeling type: text2text-generation dataset: name: fairytale_qa type: fairytale_qa ...
[ -0.0038431233260780573, -0.020483240485191345, 0.007458732929080725, 0.04212740808725357, 0.05306825786828995, 0.0029022498056292534, -0.017869556322693825, -0.0340406559407711, -0.03421076387166977, 0.03809744119644165, 0.022134674713015556, -0.016851002350449562, -0.0005963348085060716, ...
AnonymousSub/rule_based_roberta_twostagetriplet_epochs_1_shard_1_squad2.0
[ "pytorch", "roberta", "question-answering", "transformers", "autotrain_compatible" ]
question-answering
{ "architectures": [ "RobertaForQuestionAnswering" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_re...
4
null
--- library_name: stable-baselines3 tags: - LunarLander-v2 - deep-reinforcement-learning - reinforcement-learning - stable-baselines3 model-index: - name: PPO results: - metrics: - type: mean_reward value: 72.20 +/- 114.39 name: mean_reward task: type: reinforcement-learning name: re...
[ -0.039761535823345184, -0.004526308737695217, -0.00630103750154376, 0.02699519321322441, 0.04393639788031578, -0.01713859848678112, -0.007323683705180883, -0.026811037212610245, -0.03600047901272774, 0.06542667746543884, 0.030673526227474213, -0.02307078428566456, 0.022914230823516846, 0.0...
AnonymousSub/rule_based_roberta_twostagetriplet_epochs_1_shard_1_wikiqa
[ "pytorch", "roberta", "text-classification", "transformers" ]
text-classification
{ "architectures": [ "RobertaForSequenceClassification" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "...
24
null
--- tags: - Taxi-v3 - q-learning - reinforcement-learning - custom-implementation model-index: - name: q-Taxi-v3 results: - metrics: - type: mean_reward value: 7.52 +/- 2.76 name: mean_reward task: type: reinforcement-learning name: reinforcement-learning dataset: name: Tax...
[ -0.020776433870196342, -0.015481439419090748, -0.006689790170639753, 0.02949751913547516, 0.046770237386226654, -0.001349127385765314, -0.01941969059407711, 0.0020561390556395054, -0.042579300701618195, 0.05667968466877937, 0.012197896838188171, -0.014471962116658688, 0.009610778652131557, ...
AnonymousSub/rule_based_roberta_twostagetriplet_hier_epochs_1_shard_10
[ "pytorch", "roberta", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "RobertaModel" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
6
null
Access to model kabelomalapane/En-Ts_update is restricted and you are not in the authorized list. Visit https://huggingface.co/kabelomalapane/En-Ts_update to ask for access.
[ -0.04650380089879036, -0.009407642297446728, 0.028645141050219536, 0.027494190260767937, 0.0715063139796257, 0.003469347720965743, -0.001408358570188284, 0.02029978111386299, -0.0355665385723114, 0.04738437384366989, 0.035297006368637085, -0.03176124766469002, 0.03003162331879139, 0.045818...
AnonymousSub/unsup-consert-papers-bert
[ "pytorch", "bert", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "BertModel" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": nul...
9
null
--- library_name: stable-baselines3 tags: - MsPacmanNoFrameskip-v4 - deep-reinforcement-learning - reinforcement-learning - stable-baselines3 model-index: - name: QRDQN results: - metrics: - type: mean_reward value: 1209.00 +/- 822.50 name: mean_reward task: type: reinforcement-learning ...
[ -0.029648270457983017, -0.007947683334350586, -0.02491063065826893, 0.04235813394188881, 0.041366010904312134, 0.003946981858462095, -0.01131812110543251, -0.012795612215995789, -0.03296982869505882, 0.05698194354772568, 0.02101544290781021, -0.03105505183339119, 0.02197536826133728, 0.015...
AnonymousSub/unsup-consert-papers
[ "pytorch", "bert", "feature-extraction", "transformers" ]
feature-extraction
{ "architectures": [ "BertModel" ], "model_type": "bert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": nul...
2
null
--- language: - de tags: - generated_from_trainer metrics: - rouge model-index: - name: DistilBART_CNN_GNAD 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. --> # Dis...
[ -0.01781751587986946, -0.007178426720201969, -0.029422253370285034, 0.04045197367668152, 0.050096672028303146, 0.02605118416249752, -0.025086650624871254, -0.022145140916109085, -0.043227437883615494, 0.06528979539871216, 0.03038041479885578, -0.024666331708431244, -0.013019355945289135, 0...
AnonymousSubmission/pretrained-model-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
--- library_name: stable-baselines3 tags: - LunarLander-v2 - deep-reinforcement-learning - reinforcement-learning - stable-baselines3 model-index: - name: PPO results: - metrics: - type: mean_reward value: 269.16 +/- 19.09 name: mean_reward task: type: reinforcement-learning name: re...
[ -0.03993844985961914, -0.005437860265374184, -0.005758472718298435, 0.026529742404818535, 0.04408648982644081, -0.016894297674298286, -0.007495283614844084, -0.02624385617673397, -0.03673991560935974, 0.0657314583659172, 0.030325990170240402, -0.022114844992756844, 0.023695137351751328, 0....
Anorak/nirvana
[ "pytorch", "pegasus", "text2text-generation", "unk", "dataset:Anorak/autonlp-data-Niravana-test2", "transformers", "autonlp", "co2_eq_emissions", "autotrain_compatible" ]
text2text-generation
{ "architectures": [ "PegasusForConditionalGeneration" ], "model_type": "pegasus", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "n...
7
2022-08-05T19:54:52Z
--- license: apache-2.0 --- # Introduction The automatic paraphrasing model described and used in the paper "[AutoQA: From Databases to QA Semantic Parsers with Only Synthetic Training Data](https://arxiv.org/abs/2010.04806)" (EMNLP 2020). # Training data A cleaned version of the ParaBank 2 dataset introduced in "[La...
[ 0.013981141149997711, -0.02277868427336216, -0.03683975338935852, 0.07389114797115326, 0.04105619341135025, 0.01587083749473095, 0.008391445502638817, 0.021435223519802094, -0.05200067162513733, 0.06338277459144592, 0.02308911830186844, 0.006290986202657223, 0.018218792974948883, 0.0402238...
AnthonyNelson/DialoGPT-small-ricksanchez
[ "pytorch", "gpt2", "text-generation", "transformers", "conversational" ]
conversational
{ "architectures": [ "GPT2LMHeadModel" ], "model_type": "gpt2", "task_specific_params": { "conversational": { "max_length": 1000 }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
12
null
--- license: apache-2.0 tags: - generated_from_trainer metrics: - accuracy model-index: - name: distilbert-base-uncased-finetuned-mnli 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 remo...
[ -0.02986210584640503, 0.012633610516786575, -0.0305333249270916, 0.0472729317843914, 0.0464334599673748, 0.019975928589701653, -0.018428761512041092, -0.030630551278591156, -0.04166051000356674, 0.055672336369752884, 0.044148825109004974, -0.02939705178141594, 0.013128363527357578, 0.03604...
Anthos23/FS-distilroberta-fine-tuned
[ "pytorch", "roberta", "text-classification", "transformers", "has_space" ]
text-classification
{ "architectures": [ "RobertaForSequenceClassification" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "...
33
null
--- license: mit 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...
[ -0.0345640666782856, -0.01540936529636383, 0.003839387558400631, 0.02956835925579071, 0.02430683746933937, 0.020666833966970444, -0.01836133562028408, -0.008094485849142075, -0.03016383945941925, 0.04567998647689819, 0.024780988693237305, -0.051993440836668015, 0.008769826963543892, 0.0334...
Anthos23/my-awesome-model
[ "pytorch", "tf", "roberta", "text-classification", "transformers" ]
text-classification
{ "architectures": [ "RobertaForSequenceClassification" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "...
30
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:...
[ -0.02406744845211506, -0.001510528032667935, 0.004347589798271656, 0.019462259486317635, 0.02647400088608265, 0.02257336489856243, -0.017700156196951866, -0.009158313274383545, -0.015143289230763912, 0.04444670304656029, 0.024502459913492203, -0.04544169455766678, 0.018886474892497063, 0.0...
AntonClaesson/movie-plot-generator
[ "pytorch", "gpt2", "text-generation", "transformers" ]
text-generation
{ "architectures": [ "GPT2LMHeadModel" ], "model_type": "gpt2", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
9
null
--- license: apache-2.0 tags: - generated_from_trainer datasets: - imdb model-index: - name: distilbert-base-uncased-finetuned-imdb results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove ...
[ -0.016262374818325043, 0.0062826634384691715, -0.03367748484015465, 0.046329841017723083, 0.04647136107087135, 0.026484401896595955, -0.01981184259057045, -0.025963937863707542, -0.030492963269352913, 0.06585577875375748, 0.04678184539079666, -0.025172283872961998, 0.013818474486470222, 0....
Antony/mint_model
[]
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-en results: - task: name: Token Classification type: token-classification dataset: name: xtreme type: xtreme args: PAN-X.en metrics: - name:...
[ -0.024596843868494034, -0.0022157144267112017, 0.006320632062852383, 0.022602824494242668, 0.029425261542201042, 0.02300499938428402, -0.022442413493990898, -0.01171185914427042, -0.02357625588774681, 0.04693995788693428, 0.019673872739076614, -0.04623328149318695, 0.01508997194468975, 0.0...
Anubhav23/indianlegal
[]
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-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....
[ -0.041024502366781235, -0.009651534259319305, 0.0033157893922179937, 0.0334397554397583, 0.022747570648789406, 0.023110423237085342, -0.01760650984942913, -0.004392801318317652, -0.027440248057246208, 0.047508999705314636, 0.02596946619451046, -0.049315445125103, 0.020232396200299263, 0.03...
Anubhav23/model_name
[]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
null
## Model Overview This model is a Morse Code recognition model. It was trained with the package at https://github.com/1-800-BAD-CODE/MorseCodeToolkit. This model accepts as input audio signals sampled at 8khz containing Morse code. The model produces the English transcription of the Morse code signal. For inference,...
[ -0.05158461257815361, -0.03052482381463051, -0.011534960940480232, 0.044382333755493164, 0.042834289371967316, 0.021468911319971085, -0.0064388723112642765, -0.005839959718286991, -0.04871980845928192, 0.05510038137435913, 0.03936472907662392, -0.02016437239944935, -0.009388132952153683, 0...
Anupam/QuestionClassifier
[]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
null
--- library_name: stable-baselines3 tags: - LunarLander-v2 - deep-reinforcement-learning - reinforcement-learning - stable-baselines3 model-index: - name: PPO results: - metrics: - type: mean_reward value: 277.89 +/- 25.46 name: mean_reward task: type: reinforcement-learning name: re...
[ -0.03981320932507515, -0.004847873467952013, -0.006071269512176514, 0.026462601497769356, 0.04386536404490471, -0.017049280926585197, -0.007242492865771055, -0.026255356147885323, -0.03614221513271332, 0.06560146808624268, 0.03073715604841709, -0.023229416459798813, 0.023307427763938904, 0...
Apisate/Discord-Ai-Bot
[ "pytorch", "gpt2", "text-generation", "transformers" ]
text-generation
{ "architectures": [ "GPT2LMHeadModel" ], "model_type": "gpt2", "task_specific_params": { "conversational": { "max_length": 1000 }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size...
11
null
``` from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("BigSalmon/InformalToFormalLincoln61Paraphrase") model = AutoModelForCausalLM.from_pretrained("BigSalmon/InformalToFormalLincoln61Paraphrase") ``` ``` Demo: https://huggingface.co/spaces/BigSalmon/FormalInform...
[ -0.023032329976558685, -0.022970540449023247, -0.051420971751213074, 0.05906623974442482, 0.04528331384062767, 0.04955405741930008, -0.021294966340065002, -0.011475916020572186, -0.042823005467653275, 0.06816878914833069, 0.022509252652525902, -0.0010820988100022078, -0.0006945410859771073, ...
Apoorva/k2t-test
[ "pytorch", "t5", "text2text-generation", "en", "transformers", "keytotext", "k2t", "Keywords to Sentences", "autotrain_compatible" ]
text2text-generation
{ "architectures": [ "T5ForConditionalGeneration" ], "model_type": "t5", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": true, "length_penalty": 2, "max_length": 200, "min_length": 30, "no_repeat_ngram_s...
7
2022-08-05T22:23:55Z
--- license: apache-2.0 --- [Optimum Habana](https://github.com/huggingface/optimum-habana) is the interface between the Hugging Face Transformers and Diffusers libraries and Habana's Gaudi processor (HPU). It provides a set of tools enabling easy and fast model loading, training and inference on single- and multi-HPU...
[ -0.04589495062828064, -0.016732558608055115, 0.0016925404779613018, 0.03187021613121033, 0.00852280668914318, 0.028567319735884666, -0.01592126116156578, -0.01915794052183628, -0.000013399958334048279, 0.051537707448005676, 0.009515167213976383, 0.0034039372112601995, 0.02671477571129799, ...
Appolo/TestModel
[]
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: roberta-base-EnglishLawAI_roberta_base_version4 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. -...
[ -0.027897832915186882, 0.0030342747922986746, -0.009788725525140762, 0.03461156040430069, 0.0334656648337841, 0.02736145257949829, -0.012786817736923695, -0.017423013225197792, -0.05128861591219902, 0.053517475724220276, 0.007162095047533512, -0.042119015008211136, 0.02004975825548172, 0.0...
ArBert/albert-base-v2-finetuned-ner-gmm
[ "pytorch", "tensorboard", "albert", "token-classification", "transformers", "autotrain_compatible" ]
token-classification
{ "architectures": [ "AlbertForTokenClassification" ], "model_type": "albert", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_re...
8
null
--- language: en thumbnail: http://www.huggingtweets.com/chipflake/1659739094566/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...
[ -0.004074038937687874, -0.032029978930950165, 0.012172941118478775, 0.04236192628741264, 0.04634274169802666, 0.001480847829952836, -0.010756691917777061, -0.005628661252558231, -0.05012097582221031, 0.039021946489810944, 0.010118324309587479, 0.0028725594747811556, -0.00627456558868289, 0...
ArBert/bert-base-uncased-finetuned-ner-gmm
[]
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: - LunarLander-v2 - ppo - deep-reinforcement-learning - reinforcement-learning - custom-implementation - deep-rl-class model-index: - name: PPO results: - metrics: - type: mean_reward value: 103.08 +/- 43.38 name: mean_reward task: type: reinforcement-learning name: reinforc...
[ -0.017440564930438995, 0.013999531976878643, -0.005144219379872084, 0.016862599179148674, 0.052761439234018326, -0.025024360045790672, 0.005486298818141222, -0.03553284332156181, -0.01304977759718895, 0.06839166581630707, 0.027577105909585953, -0.022378137335181236, 0.004197562579065561, 0...
ArBert/roberta-base-finetuned-ner-kmeans-twitter
[ "pytorch", "tensorboard", "roberta", "token-classification", "transformers", "generated_from_trainer", "license:mit", "autotrain_compatible" ]
token-classification
{ "architectures": [ "RobertaForTokenClassification" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_...
10
2022-08-05T23:42:30Z
--- tags: - CartPole-v1 - ppo - deep-reinforcement-learning - reinforcement-learning - custom-implementation - deep-rl-class model-index: - name: PPO results: - metrics: - type: mean_reward value: 166.60 +/- 82.10 name: mean_reward task: type: reinforcement-learning name: reinforceme...
[ -0.015381267294287682, 0.003786753863096237, -0.013599484227597713, 0.01714354008436203, 0.04758164659142494, -0.004317631013691425, -0.0013002814957872033, -0.023468278348445892, -0.018165241926908493, 0.07667282968759537, 0.0019037534948438406, -0.01918693445622921, -0.0009222517255693674,...
ArBert/roberta-base-finetuned-ner
[ "pytorch", "tensorboard", "roberta", "token-classification", "transformers", "generated_from_trainer", "license:mit", "autotrain_compatible" ]
token-classification
{ "architectures": [ "RobertaForTokenClassification" ], "model_type": "roberta", "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_...
3
null
--- language: en thumbnail: https://github.com/borisdayma/huggingtweets/blob/master/img/logo.png?raw=true tags: - huggingtweets widget: - text: "My dream is" --- <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:inherit; margin-left: 4px; margin-right: 4...
[ 0.009710763581097126, -0.03208238631486893, 0.001012982800602913, 0.04112087935209274, 0.05102451518177986, 0.01439167931675911, -0.02677382156252861, -0.009119581431150436, -0.034859467297792435, 0.03788824751973152, -0.0021731737069785595, -0.005015421658754349, 0.004819836933165789, 0.0...
ArJakusz/DialoGPT-small-stark
[ "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...
8
null
--- language: en thumbnail: http://www.huggingtweets.com/shyamalanadkat/1659744994175/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; ...
[ 0.006235276814550161, -0.035728417336940765, 0.003870314219966531, 0.05282444879412651, 0.04886408522725105, 0.02032748982310295, -0.014797449111938477, -0.0023798923939466476, -0.04021753370761871, 0.03997832164168358, 0.01617705635726452, -0.004986434243619442, -0.005758150480687618, 0.0...
ArJakusz/DialoGPT-small-starky
[]
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: other tags: - generated_from_trainer metrics: - accuracy model-index: - name: output results: [] --- # MonoGPTari-1.3b This model is a fine-tuned version of [facebook/opt-1.3b](https://huggingface.co/facebook/opt-1.3b) on an english monogatari text dataset. This was primarily used as a PoC, use the ...
[ -0.013793965801596642, -0.0189069714397192, -0.007132247556000948, 0.05950859934091568, 0.045200034976005554, 0.02845720387995243, 0.0092008663341403, -0.011354777961969376, -0.03900337219238281, 0.06204724684357643, 0.0521763451397419, -0.0043740952387452126, 0.02633049339056015, 0.031411...
Araby/Arabic-TTS
[]
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: other tags: - generated_from_trainer metrics: - accuracy model-index: - name: output_2 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. --> # monogptari-...
[ -0.018503835424780846, -0.009437637403607368, -0.004903451073914766, 0.054887112230062485, 0.04109431058168411, 0.032622430473566055, 0.0065200780518352985, -0.022203557193279266, -0.04863571748137474, 0.0697687566280365, 0.05302261561155319, -0.013213012367486954, 0.032506756484508514, 0....
Aran/DialoGPT-small-harrypotter
[ "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...
8
null
--- license: apache-2.0 tags: - generated_from_trainer datasets: - emotion metrics: - accuracy - f1 model-index: - name: distilbert-base-uncased-finetuned-emotion results: - task: name: Text Classification type: text-classification dataset: name: emotion type: emotion args: default...
[ -0.00853502843528986, 0.009707113727927208, -0.029414106160402298, 0.03710170090198517, 0.061036475002765656, 0.033688023686409, -0.024028364568948746, -0.03529493510723114, -0.03352716937661171, 0.0558602400124073, 0.019914286211133003, -0.046672362834215164, 0.03521209582686424, 0.042776...
ArashEsk95/bert-base-uncased-finetuned-stsb
[]
null
{ "architectures": null, "model_type": null, "task_specific_params": { "conversational": { "max_length": null }, "summarization": { "early_stopping": null, "length_penalty": null, "max_length": null, "min_length": null, "no_repeat_ngram_size": null, "num_beams...
0
null
--- license: apache-2.0 tags: - generated_from_trainer datasets: - squad_v2 model-index: - name: albert-base-v2-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 remove this...
[ -0.029163841158151627, -0.02131679281592369, -0.01671737991273403, 0.04389301314949989, 0.04545784741640091, 0.006695708259940147, -0.027663957327604294, 0.013409911654889584, -0.029719073325395584, 0.04128778353333473, 0.04150116816163063, -0.016429085284471512, 0.0075799147598445415, 0.0...