Instructions to use clicknext/phayathaibert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use clicknext/phayathaibert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="clicknext/phayathaibert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("clicknext/phayathaibert") model = AutoModelForMaskedLM.from_pretrained("clicknext/phayathaibert") - Notebooks
- Google Colab
- Kaggle
edit model_max_length
Browse files- tokenizer_config.json +1 -1
tokenizer_config.json
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@@ -16,7 +16,7 @@
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"rstrip": false,
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"single_word": false
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},
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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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"sp_model_kwargs": {},
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"rstrip": false,
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"single_word": false
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},
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"model_max_length": 510,
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"pad_token": "<pad>",
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"sep_token": "</s>",
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"sp_model_kwargs": {},
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