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
Commit History
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Update README.md
Verified signatured87cb78
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (a1f57d9cb66bc018f46972e608ec2260c5de35dc) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>02f94ba
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fix: only use token_type id 0 for fast tokenizer
67dd433 -
feat: add fast tokenizer
* also fix tokenizer_configcb6e01e -
docs: inference api template
e9af171 -
docs: update readme
9e8a544 -
docs: add readme
2dbb973
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fix: model_max_length to 512
baa355e -
fix: model_max_length to 514
james.ryu41b3d9b -
fix: model_max_length to 514
james.ryu436ec9c
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fix: several issues
* change special token location on vocab.txt * add bos_token & eos_tokenaf74d6b
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feat: Upload model
8b7c38a -
initial commit
d5ebfba