Instructions to use klue/roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use klue/roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="klue/roberta-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("klue/roberta-base") model = AutoModelForMaskedLM.from_pretrained("klue/roberta-base", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
fix: model_max_length to 512
Browse files- tokenizer_config.json +1 -1
tokenizer_config.json
CHANGED
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@@ -11,5 +11,5 @@
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"eos_token": "[SEP]",
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"tokenize_chinese_chars": true,
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"strip_accents": null,
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-
"model_max_length":
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}
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"eos_token": "[SEP]",
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"tokenize_chinese_chars": true,
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"strip_accents": null,
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+
"model_max_length": 512
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}
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