Instructions to use CCTD/LLM_Favrskov with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CCTD/LLM_Favrskov with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CCTD/LLM_Favrskov")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CCTD/LLM_Favrskov") model = AutoModelForSequenceClassification.from_pretrained("CCTD/LLM_Favrskov", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update tokenizer_config.json
Browse files- tokenizer_config.json +1 -5
tokenizer_config.json
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@@ -51,9 +51,5 @@
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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"tokenizer_class": "BertTokenizer",
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"unk_token": "[UNK]"
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"truncation": true,
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"padding": "max_length",
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"max_length": 256,
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"return_tensors": "pt"
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}
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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"tokenizer_class": "BertTokenizer",
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"unk_token": "[UNK]"
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}
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