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@ -80,10 +80,11 @@ class AutoTransformers(NNOperator): |
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if path == 'default': |
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path = str(Path(__file__).parent) |
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name = self.model_name.replace('/', '-') |
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path = os.path.join(path, name + '.pt') |
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path = os.path.join(path, name) |
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inputs = self.tokenizer('[CLS]', return_tensors='pt') |
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inputs = list(inputs.values()) |
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if format == 'torchscript': |
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path = path + '.pt' |
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inputs = list(inputs.values()) |
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try: |
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try: |
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jit_model = torch.jit.script(self.model) |
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@ -93,127 +94,139 @@ class AutoTransformers(NNOperator): |
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except Exception as e: |
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log.error(f'Fail to save as torchscript: {e}.') |
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raise RuntimeError(f'Fail to save as torchscript: {e}.') |
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elif format == 'onxx': |
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pass |
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else: |
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torch.save(self.model, path) |
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def get_model_list(): |
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full_list = [ |
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"bert-large-uncased", |
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"bert-base-cased", |
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"bert-large-cased", |
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"bert-base-multilingual-uncased", |
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"bert-base-multilingual-cased", |
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"bert-base-chinese", |
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"bert-base-german-cased", |
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"bert-large-uncased-whole-word-masking", |
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"bert-large-cased-whole-word-masking", |
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"bert-large-uncased-whole-word-masking-finetuned-squad", |
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"bert-large-cased-whole-word-masking-finetuned-squad", |
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"bert-base-cased-finetuned-mrpc", |
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"bert-base-german-dbmdz-cased", |
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"bert-base-german-dbmdz-uncased", |
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"cl-tohoku/bert-base-japanese-whole-word-masking", |
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"cl-tohoku/bert-base-japanese-char", |
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"cl-tohoku/bert-base-japanese-char-whole-word-masking", |
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"TurkuNLP/bert-base-finnish-cased-v1", |
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"TurkuNLP/bert-base-finnish-uncased-v1", |
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"wietsedv/bert-base-dutch-cased", |
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"google/bigbird-roberta-base", |
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"google/bigbird-roberta-large", |
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"google/bigbird-base-trivia-itc", |
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"albert-base-v1", |
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"albert-large-v1", |
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"albert-xlarge-v1", |
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"albert-xxlarge-v1", |
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"albert-base-v2", |
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"albert-large-v2", |
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"albert-xlarge-v2", |
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"albert-xxlarge-v2", |
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"facebook/bart-large", |
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"google/bert_for_seq_generation_L-24_bbc_encoder", |
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"google/bigbird-pegasus-large-arxiv", |
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"google/bigbird-pegasus-large-pubmed", |
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"google/bigbird-pegasus-large-bigpatent", |
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"google/canine-s", |
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"google/canine-c", |
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"YituTech/conv-bert-base", |
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"YituTech/conv-bert-medium-small", |
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"YituTech/conv-bert-small", |
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"ctrl", |
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"microsoft/deberta-base", |
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"microsoft/deberta-large", |
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"microsoft/deberta-xlarge", |
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"microsoft/deberta-base-mnli", |
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"microsoft/deberta-large-mnli", |
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"microsoft/deberta-xlarge-mnli", |
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"distilbert-base-uncased", |
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"distilbert-base-uncased-distilled-squad", |
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"distilbert-base-cased", |
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"distilbert-base-cased-distilled-squad", |
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"distilbert-base-german-cased", |
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"distilbert-base-multilingual-cased", |
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"distilbert-base-uncased-finetuned-sst-2-english", |
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"google/electra-small-generator", |
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"google/electra-base-generator", |
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"google/electra-large-generator", |
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"google/electra-small-discriminator", |
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"google/electra-base-discriminator", |
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"google/electra-large-discriminator", |
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"google/fnet-base", |
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"google/fnet-large", |
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"facebook/wmt19-ru-en", |
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"funnel-transformer/small", |
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"funnel-transformer/small-base", |
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"funnel-transformer/medium", |
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"funnel-transformer/medium-base", |
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"funnel-transformer/intermediate", |
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"funnel-transformer/intermediate-base", |
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"funnel-transformer/large", |
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"funnel-transformer/large-base", |
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"funnel-transformer/xlarge-base", |
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"funnel-transformer/xlarge", |
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"gpt2", |
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"gpt2-medium", |
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"gpt2-large", |
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"gpt2-xl", |
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"distilgpt2", |
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"EleutherAI/gpt-neo-1.3B", |
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"EleutherAI/gpt-j-6B", |
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"kssteven/ibert-roberta-base", |
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"allenai/led-base-16384", |
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"google/mobilebert-uncased", |
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"microsoft/mpnet-base", |
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"uw-madison/nystromformer-512", |
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"openai-gpt", |
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"google/reformer-crime-and-punishment", |
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"tau/splinter-base", |
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"tau/splinter-base-qass", |
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"tau/splinter-large", |
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"tau/splinter-large-qass", |
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"squeezebert/squeezebert-uncased", |
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"squeezebert/squeezebert-mnli", |
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"squeezebert/squeezebert-mnli-headless", |
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"transfo-xl-wt103", |
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"xlm-mlm-en-2048", |
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"xlm-mlm-ende-1024", |
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"xlm-mlm-enfr-1024", |
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"xlm-mlm-enro-1024", |
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"xlm-mlm-tlm-xnli15-1024", |
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"xlm-mlm-xnli15-1024", |
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"xlm-clm-enfr-1024", |
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"xlm-clm-ende-1024", |
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"xlm-mlm-17-1280", |
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"xlm-mlm-100-1280", |
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"xlm-roberta-base", |
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"xlm-roberta-large", |
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"xlm-roberta-large-finetuned-conll02-dutch", |
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"xlm-roberta-large-finetuned-conll02-spanish", |
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"xlm-roberta-large-finetuned-conll03-english", |
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"xlm-roberta-large-finetuned-conll03-german", |
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"xlnet-base-cased", |
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"xlnet-large-cased", |
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"uw-madison/yoso-4096", |
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] |
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full_list.sort() |
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return full_list |
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def get_model_name(self): |
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full_list = [ |
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"bert-large-uncased", |
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"bert-base-cased", |
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"bert-large-cased", |
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"bert-base-multilingual-uncased", |
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"bert-base-multilingual-cased", |
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"bert-base-chinese", |
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"bert-base-german-cased", |
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"bert-large-uncased-whole-word-masking", |
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"bert-large-cased-whole-word-masking", |
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"bert-large-uncased-whole-word-masking-finetuned-squad", |
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"bert-large-cased-whole-word-masking-finetuned-squad", |
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"bert-base-cased-finetuned-mrpc", |
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"bert-base-german-dbmdz-cased", |
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"bert-base-german-dbmdz-uncased", |
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"cl-tohoku/bert-base-japanese-whole-word-masking", |
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"cl-tohoku/bert-base-japanese-char", |
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"cl-tohoku/bert-base-japanese-char-whole-word-masking", |
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"TurkuNLP/bert-base-finnish-cased-v1", |
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"TurkuNLP/bert-base-finnish-uncased-v1", |
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"wietsedv/bert-base-dutch-cased", |
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"google/bigbird-roberta-base", |
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"google/bigbird-roberta-large", |
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"google/bigbird-base-trivia-itc", |
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"albert-base-v1", |
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"albert-large-v1", |
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"albert-xlarge-v1", |
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"albert-xxlarge-v1", |
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"albert-base-v2", |
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"albert-large-v2", |
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"albert-xlarge-v2", |
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"albert-xxlarge-v2", |
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"facebook/bart-large", |
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"google/bert_for_seq_generation_L-24_bbc_encoder", |
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"google/bigbird-pegasus-large-arxiv", |
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"google/bigbird-pegasus-large-pubmed", |
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"google/bigbird-pegasus-large-bigpatent", |
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"google/canine-s", |
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"google/canine-c", |
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"YituTech/conv-bert-base", |
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"YituTech/conv-bert-medium-small", |
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"YituTech/conv-bert-small", |
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"ctrl", |
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"microsoft/deberta-base", |
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"microsoft/deberta-large", |
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"microsoft/deberta-xlarge", |
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"microsoft/deberta-base-mnli", |
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"microsoft/deberta-large-mnli", |
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"microsoft/deberta-xlarge-mnli", |
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"distilbert-base-uncased", |
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"distilbert-base-uncased-distilled-squad", |
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"distilbert-base-cased", |
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"distilbert-base-cased-distilled-squad", |
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"distilbert-base-german-cased", |
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"distilbert-base-multilingual-cased", |
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"distilbert-base-uncased-finetuned-sst-2-english", |
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"google/electra-small-generator", |
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"google/electra-base-generator", |
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"google/electra-large-generator", |
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"google/electra-small-discriminator", |
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"google/electra-base-discriminator", |
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"google/electra-large-discriminator", |
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"google/fnet-base", |
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"google/fnet-large", |
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"facebook/wmt19-ru-en", |
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"funnel-transformer/small", |
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"funnel-transformer/small-base", |
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"funnel-transformer/medium", |
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"funnel-transformer/medium-base", |
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"funnel-transformer/intermediate", |
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"funnel-transformer/intermediate-base", |
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"funnel-transformer/large", |
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"funnel-transformer/large-base", |
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"funnel-transformer/xlarge-base", |
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"funnel-transformer/xlarge", |
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"gpt2", |
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"gpt2-medium", |
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"gpt2-large", |
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"gpt2-xl", |
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"distilgpt2", |
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"EleutherAI/gpt-neo-1.3B", |
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"EleutherAI/gpt-j-6B", |
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"kssteven/ibert-roberta-base", |
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"allenai/led-base-16384", |
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"google/mobilebert-uncased", |
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"microsoft/mpnet-base", |
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"uw-madison/nystromformer-512", |
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"openai-gpt", |
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"google/reformer-crime-and-punishment", |
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"tau/splinter-base", |
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"tau/splinter-base-qass", |
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"tau/splinter-large", |
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"tau/splinter-large-qass", |
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"squeezebert/squeezebert-uncased", |
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"squeezebert/squeezebert-mnli", |
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"squeezebert/squeezebert-mnli-headless", |
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"transfo-xl-wt103", |
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"xlm-mlm-en-2048", |
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"xlm-mlm-ende-1024", |
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"xlm-mlm-enfr-1024", |
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"xlm-mlm-enro-1024", |
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"xlm-mlm-tlm-xnli15-1024", |
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"xlm-mlm-xnli15-1024", |
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"xlm-clm-enfr-1024", |
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"xlm-clm-ende-1024", |
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"xlm-mlm-17-1280", |
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"xlm-mlm-100-1280", |
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"xlm-roberta-base", |
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"xlm-roberta-large", |
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"xlm-roberta-large-finetuned-conll02-dutch", |
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"xlm-roberta-large-finetuned-conll02-spanish", |
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"xlm-roberta-large-finetuned-conll03-english", |
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"xlm-roberta-large-finetuned-conll03-german", |
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"xlnet-base-cased", |
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"xlnet-large-cased", |
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"uw-madison/yoso-4096", |
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"microsoft/deberta-v2-xlarge", |
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"microsoft/deberta-v2-xxlarge", |
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"microsoft/deberta-v2-xlarge-mnli", |
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"microsoft/deberta-v2-xxlarge-mnli", |
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"flaubert/flaubert_small_cased", |
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"flaubert/flaubert_base_uncased", |
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"flaubert/flaubert_base_cased", |
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"flaubert/flaubert_large_cased", |
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"camembert-base", |
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"Musixmatch/umberto-commoncrawl-cased-v1", |
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"Musixmatch/umberto-wikipedia-uncased-v1", |
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] |
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full_list.sort() |
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return full_list |
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