Instructions to use huggingface/CodeBERTa-small-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use huggingface/CodeBERTa-small-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="huggingface/CodeBERTa-small-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("huggingface/CodeBERTa-small-v1") model = AutoModelForMaskedLM.from_pretrained("huggingface/CodeBERTa-small-v1") - Inference
- Notebooks
- Google Colab
- Kaggle
Add TF weights (#1)
Browse files- Add TF weights (fd24e75d62070a4767d5f11d78d64b17874da063)
Co-authored-by: Joao Gante <joaogante@users.noreply.huggingface.co>
- tf_model.h5 +3 -0
tf_model.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:bfcb331cb21d8a646606a33f87446394d79a24e1f03f12cc5d40c70d4d9556a5
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size 495505384
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