Instructions to use crochereau/lobster-mgm-11M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use crochereau/lobster-mgm-11M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="crochereau/lobster-mgm-11M")# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("crochereau/lobster-mgm-11M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload tokenizer
Browse files- special_tokens_map.json +9 -0
- tokenizer_config.json +17 -0
- vocab.txt +68 -0
special_tokens_map.json
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{
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"bos_token": "<bos>",
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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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"sep_token": "<sep>",
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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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"added_tokens_decoder": {},
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"bos_token": "<bos>",
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"clean_up_tokenization_spaces": true,
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"cls_df": "<cls_sf>",
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"cls_dna": "<cls_dna>",
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"cls_prot": "<cls_prot>",
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"cls_token": "<cls>",
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"do_lower_case": false,
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"eos_token": "<eos>",
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"mask_token": "<mask>",
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"model_max_length": 1000000000000000019884624838656,
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"pad_token": "<pad>",
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"sep_token": "<sep>",
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"tokenizer_class": "MgmTokenizer",
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"unk_token": "<unk>"
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}
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vocab.txt
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<bos>
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<cls>
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<cls_aa>
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<cls_nt>
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<cls_sf>
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<cls_struct>
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<eos>
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<mask>
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<null_1>
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<pad>
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<reserved>
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<sep>
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<unk>
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[Branch3]
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[#Branch1]
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[=Branch2]
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