Model and configs
Browse files- README.md +32 -0
- config.json +74 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +1 -0
- tokenizer.json +0 -0
- tokenizer_config.json +4 -0
README.md
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The repository is adapted based on: https://huggingface.co/chenxran/bart-smiles/tree/main
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```python
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from transformers import AutoTokenizer, AutoModel, SequenceFeatureExtractor
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import torch
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from transformers import AutoTokenizer, AutoModel
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smiles = "CCC(=O)"
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tokenizer = AutoTokenizer.from_pretrained("./BARTSmiles/", add_prefix_space=True)
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inputs = tokenizer(smiles, return_tensors="pt", return_token_type_ids=False, add_special_tokens=True)
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model = AutoModel.from_pretrained('./BARTSmiles')
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model.eval()
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# Use a pipeline as a high-level helper
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from transformers import pipeline
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extractor = pipeline("feature-extraction", model=model, tokenizer=tokenizer)
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result = extractor(smiles, return_tensors=True, tokenize_kwargs={'return_token_type_ids':False})
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```
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## Citation
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@article{chilingaryan2022bartsmiles,
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title={Bartsmiles: Generative masked language models for molecular representations},
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author={Chilingaryan, Gayane and Tamoyan, Hovhannes and Tevosyan, Ani and Babayan, Nelly and Khondkaryan, Lusine and Hambardzumyan, Karen and Navoyan, Zaven and Khachatrian, Hrant and Aghajanyan, Armen},
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journal={arXiv preprint arXiv:2211.16349},
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year={2022}
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}
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config.json
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{
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"_name_or_path": "pretrained_model/bart-smiles",
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"activation_dropout": 0.1,
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"activation_function": "gelu",
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"add_bias_logits": false,
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"add_final_layer_norm": false,
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"architectures": [
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"BartModel"
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],
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"attention_dropout": 0.1,
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"bos_token_id": 0,
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"classif_dropout": 0.1,
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"classifier_dropout": 0.0,
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"d_model": 1024,
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"decoder_attention_heads": 16,
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"decoder_ffn_dim": 4096,
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"decoder_layerdrop": 0.0,
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"decoder_layers": 12,
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"decoder_start_token_id": 2,
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"dropout": 0.1,
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"early_stopping": true,
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"encoder_attention_heads": 16,
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"encoder_ffn_dim": 4096,
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"encoder_layerdrop": 0.0,
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"encoder_layers": 12,
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"eos_token_id": 2,
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"forced_bos_token_id": 0,
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"forced_eos_token_id": 2,
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"gradient_checkpointing": false,
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"id2label": {
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"0": "LABEL_0",
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"1": "LABEL_1",
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"2": "LABEL_2"
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},
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"init_std": 0.02,
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"is_encoder_decoder": true,
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"label2id": {
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"LABEL_0": 0,
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"LABEL_1": 1,
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"LABEL_2": 2
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},
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"max_position_embeddings": 128,
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"model_type": "bart",
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"no_repeat_ngram_size": 3,
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"normalize_before": false,
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"num_beams": 4,
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"num_hidden_layers": 12,
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"pad_token_id": 1,
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"scale_embedding": false,
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"task_specific_params": {
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"summarization": {
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"length_penalty": 1.0,
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"max_length": 128,
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"min_length": 12,
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"num_beams": 4
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},
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"summarization_cnn": {
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"length_penalty": 2.0,
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"max_length": 142,
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"min_length": 56,
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"num_beams": 4
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},
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"summarization_xsum": {
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"length_penalty": 1.0,
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"max_length": 62,
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"min_length": 11,
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"num_beams": 6
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}
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},
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"torch_dtype": "float32",
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"transformers_version": "4.26.1",
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"use_cache": true,
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"vocab_size": 1026
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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 sha256:97732fdbcc3c52b53c0929a76bea0311cfd8b4d18b744956243e036aac5ac652
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size 135
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special_tokens_map.json
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{}
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tokenizer.json
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tokenizer_config.json
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{
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"model_max_length": 1000000000000000019884624838656,
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"tokenizer_class": "PreTrainedTokenizerFast"
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}
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