First version of the your-model-name model and tokenizer.
Browse files- SquadQA +0 -1
- __pycache__/preprocess.cpython-37.pyc +0 -0
- config.json +23 -0
- main.py +2 -2
- pytorch_model.bin +3 -0
- special_tokens_map.json +1 -0
- tokenizer_config.json +1 -0
- vocab.txt +0 -0
SquadQA
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Subproject commit 4c80bc7e918707ebec6205c2c532e646f89bff7f
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__pycache__/preprocess.cpython-37.pyc
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Binary files a/__pycache__/preprocess.cpython-37.pyc and b/__pycache__/preprocess.cpython-37.pyc differ
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config.json
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{
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"_name_or_path": "distilbert-base-uncased",
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"activation": "gelu",
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"architectures": [
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"DistilBertForQuestionAnswering"
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],
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"attention_dropout": 0.1,
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"dim": 768,
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"dropout": 0.1,
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"hidden_dim": 3072,
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"initializer_range": 0.02,
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"max_position_embeddings": 512,
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"model_type": "distilbert",
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"n_heads": 12,
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"n_layers": 6,
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"pad_token_id": 0,
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"qa_dropout": 0.1,
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"seq_classif_dropout": 0.2,
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"sinusoidal_pos_embds": false,
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"tie_weights_": true,
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"transformers_version": "4.3.2",
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"vocab_size": 30522
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}
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main.py
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optim.step()
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print("Done")
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model.eval()
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model.save_pretrained("
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data.tokenizer.save_pretrained("
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subprocess.call(["git", "add","--all"])
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optim.step()
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print("Done")
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model.eval()
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model.save_pretrained("./")
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data.tokenizer.save_pretrained("./")
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subprocess.call(["git", "add","--all"])
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:0312fd8f3cd55009ac7804e8c649c21663e3de8834cc805a21259a15d8dd3917
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size 265498527
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special_tokens_map.json
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{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}
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tokenizer_config.json
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{"do_lower_case": true, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "model_max_length": 512, "name_or_path": "distilbert-base-uncased"}
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vocab.txt
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