Instructions to use Syzseisus/230905_180801 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Syzseisus/230905_180801 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Syzseisus/230905_180801")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Syzseisus/230905_180801") model = AutoModelForSequenceClassification.from_pretrained("Syzseisus/230905_180801", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
Browse files- config.json +37 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +7 -0
- tokenizer_config.json +5 -0
- training_args.bin +3 -0
- vocab.txt +33 -0
config.json
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{
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"_name_or_path": "facebook/esm2_t12_35M_UR50D",
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"architectures": [
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"EsmForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.0,
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"classifier_dropout": null,
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"emb_layer_norm_before": false,
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"esmfold_config": null,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.0,
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"hidden_size": 480,
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"id2label": {
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"0": "LABEL_0"
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},
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"initializer_range": 0.02,
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"intermediate_size": 1920,
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"is_folding_model": false,
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"label2id": {
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"LABEL_0": 0
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},
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"layer_norm_eps": 1e-05,
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"mask_token_id": 32,
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"max_position_embeddings": 1026,
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"model_type": "esm",
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"num_attention_heads": 20,
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"num_hidden_layers": 12,
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"pad_token_id": 1,
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"position_embedding_type": "rotary",
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"problem_type": "regression",
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"token_dropout": true,
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"torch_dtype": "float32",
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"transformers_version": "4.33.0",
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"use_cache": true,
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"vocab_list": null,
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"vocab_size": 33
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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 sha256:91d19d68f17f43f99ed69c67b751de1d252229d53c8041d46b55fc72f93984db
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size 136045861
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special_tokens_map.json
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{
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"cls_token": "<cls>",
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"eos_token": "<eos>",
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"mask_token": "<mask>",
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"pad_token": "<pad>",
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"unk_token": "<unk>"
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}
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tokenizer_config.json
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{
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"clean_up_tokenization_spaces": true,
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"model_max_length": 1024,
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"tokenizer_class": "EsmTokenizer"
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}
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:316e23b9ce41e0c2ebf8a25858577f1b9ca85b3400e09e8fa7ea1d6a308bb282
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size 4091
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vocab.txt
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<cls>
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<pad>
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<eos>
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<unk>
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-
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<null_1>
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<mask>
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