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:
- 64e84f90ad1a4b3a1a5ebe44db56e000c05a3c3a4b4c41c7f1e3a19065deb52b
- Size of remote file:
- 336 MB
- SHA256:
- 3835de5b46b0780d340f5ab2cb63c011d8dc94ccee35667c472bba78dcf8d923
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