Instructions to use sujalgawas/code-bert-python with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sujalgawas/code-bert-python with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="sujalgawas/code-bert-python")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("sujalgawas/code-bert-python") model = AutoModel.from_pretrained("sujalgawas/code-bert-python", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload tokenizer
Browse files- tokenizer.json +0 -0
- tokenizer_config.json +1 -1
tokenizer.json
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tokenizer_config.json
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"errors": "replace",
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"is_local": false,
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"mask_token": "<mask>",
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"model_max_length":
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"pad_token": "<pad>",
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"sep_token": "</s>",
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"tokenizer_class": "RobertaTokenizer",
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"errors": "replace",
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"is_local": false,
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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": "</s>",
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"tokenizer_class": "RobertaTokenizer",
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