Instructions to use malteklaes/based-CodeBERTa-language-id-llm-module with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use malteklaes/based-CodeBERTa-language-id-llm-module with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="malteklaes/based-CodeBERTa-language-id-llm-module")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("malteklaes/based-CodeBERTa-language-id-llm-module") model = AutoModelForSequenceClassification.from_pretrained("malteklaes/based-CodeBERTa-language-id-llm-module") - Notebooks
- Google Colab
- Kaggle
updated tokenizer on 2024-04-14, 14:36:44
Browse files- tokenizer.json +0 -0
- tokenizer_config.json +2 -0
- vocab.json +0 -0
tokenizer.json
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tokenizer_config.json
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@@ -51,7 +51,9 @@
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"max_len": 512,
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"model_max_length": 512,
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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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"unk_token": "<unk>"
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}
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"max_len": 512,
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"model_max_length": 512,
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"pad_token": "<pad>",
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"return_attention_mask": true,
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"sep_token": "</s>",
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"tokenizer_class": "RobertaTokenizer",
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"trim_offsets": true,
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"unk_token": "<unk>"
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}
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vocab.json
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