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
- Xet hash:
- 2081d55bc423c147ff6d96b6f6b0822030301392902a42b214873774a3527a51
- Size of remote file:
- 496 MB
- SHA256:
- bfcb331cb21d8a646606a33f87446394d79a24e1f03f12cc5d40c70d4d9556a5
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