Instructions to use TJMUCH/transcriptome-iseeek with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TJMUCH/transcriptome-iseeek with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="TJMUCH/transcriptome-iseeek")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("TJMUCH/transcriptome-iseeek") model = AutoModelForMaskedLM.from_pretrained("TJMUCH/transcriptome-iseeek") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): c1b88e2
commit from lixc
Browse files- special_tokens_map.json +1 -0
- tokenizer.json +0 -0
- tokenizer_config.json +1 -0
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.json
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tokenizer_config.json
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{"mask_token": "[MASK]", "cls_token": "[CLS]", "sep_token": "[SEP]", "pad_token": "[PAD]", "unk_token": "[UNK]", "tokenizer_class": "PreTrainedTokenizerFast"}
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