Instructions to use Shubhamai/tiny-bert-for-token-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shubhamai/tiny-bert-for-token-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Shubhamai/tiny-bert-for-token-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Shubhamai/tiny-bert-for-token-classification") model = AutoModelForTokenClassification.from_pretrained("Shubhamai/tiny-bert-for-token-classification") - Notebooks
- Google Colab
- Kaggle
Upload 3 files
Browse files- special_tokens_map.json +1 -0
- tokenizer_config.json +1 -0
- vocab.txt +0 -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_config.json
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{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "max_len": 512, "special_tokens_map_file": "/home/nicolas/.cache/torch/transformers/7ed0658a09e4f9689057c83f8b734d0e8d739f73461c7b7d1bc403aa451e304b.275045728fbf41c11d3dae08b8742c054377e18d92cc7b72b6351152a99b64e4", "tokenizer_file": null}
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vocab.txt
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