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:
- 669c2500ea2458e8cdeafe785179bd3ade979050ba0a6aa423830ae393f6ccea
- Size of remote file:
- 334 MB
- SHA256:
- 5d9fb3a24f25bf2caa079cb88416ed37c30bb0c4bbb7a13bc4e2515ad346d4d9
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