adding core files for protein structure model v1.2
Browse files- config.json +105 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +7 -0
- tokenizer_config.json +15 -0
- vocab.txt +0 -0
config.json
ADDED
@@ -0,0 +1,105 @@
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{
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"_name_or_path": "microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext",
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"architectures": [
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"BertForTokenClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"classifier_dropout": null,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"id2label": {
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"0": "O",
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"1": "B-chemical",
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"2": "B-species",
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"3": "B-gene",
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"4": "I-gene",
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"5": "B-taxonomy_domain",
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"6": "B-experimental_method",
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"7": "I-experimental_method",
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"8": "B-protein_type",
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"9": "I-protein_type",
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"10": "I-species",
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"11": "B-evidence",
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"12": "I-evidence",
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"13": "B-protein",
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"14": "I-protein",
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"15": "B-protein_state",
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"16": "B-site",
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"17": "I-site",
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"18": "I-chemical",
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"19": "B-complex_assembly",
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"20": "I-complex_assembly",
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"21": "I-protein_state",
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"22": "B-ptm",
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"23": "B-mutant",
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"24": "I-mutant",
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"25": "B-structure_element",
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"26": "I-structure_element",
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"27": "B-residue_range",
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"28": "I-residue_range",
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"29": "B-residue_name_number",
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"30": "B-residue_name",
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"31": "I-taxonomy_domain",
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"32": "B-oligomeric_state",
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"33": "I-oligomeric_state",
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"34": "B-residue_number",
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"35": "I-ptm",
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"36": "I-residue_name_number",
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"37": "I-residue_number"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"B-chemical": 1,
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"B-complex_assembly": 19,
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"B-evidence": 11,
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"B-experimental_method": 6,
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"B-gene": 3,
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"B-mutant": 23,
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"B-oligomeric_state": 32,
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"B-protein": 13,
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"B-protein_state": 15,
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"B-protein_type": 8,
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"B-ptm": 22,
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"B-residue_name": 30,
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"B-residue_name_number": 29,
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"B-residue_number": 34,
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"B-residue_range": 27,
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"B-site": 16,
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"B-species": 2,
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"B-structure_element": 25,
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"B-taxonomy_domain": 5,
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"I-chemical": 18,
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"I-complex_assembly": 20,
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"I-evidence": 12,
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"I-experimental_method": 7,
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"I-gene": 4,
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"I-mutant": 24,
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"I-oligomeric_state": 33,
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"I-protein": 14,
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"I-protein_state": 21,
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"I-protein_type": 9,
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"I-ptm": 35,
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"I-residue_name_number": 36,
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"I-residue_number": 37,
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"I-residue_range": 28,
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"I-site": 17,
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"I-species": 10,
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"I-structure_element": 26,
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"I-taxonomy_domain": 31,
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"O": 0
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},
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"model_type": "bert",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 0,
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"position_embedding_type": "absolute",
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"torch_dtype": "float32",
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"transformers_version": "4.28.0",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 30522
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:13282ea39dc7a99a5d68378af7b6f5c7fc898575259f6d632f5ecdb68470cf4a
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size 435755629
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special_tokens_map.json
ADDED
@@ -0,0 +1,7 @@
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{
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"cls_token": "[CLS]",
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"mask_token": "[MASK]",
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"unk_token": "[UNK]"
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}
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tokenizer_config.json
ADDED
@@ -0,0 +1,15 @@
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{
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"clean_up_tokenization_spaces": true,
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"cls_token": "[CLS]",
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"do_basic_tokenize": true,
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"do_lower_case": true,
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"mask_token": "[MASK]",
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"model_max_length": 1000000000000000019884624838656,
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"never_split": null,
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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"tokenizer_class": "BertTokenizer",
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"unk_token": "[UNK]"
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}
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vocab.txt
ADDED
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