Instructions to use mrm8488/codeBERTaJS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/codeBERTaJS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="mrm8488/codeBERTaJS")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("mrm8488/codeBERTaJS") model = AutoModelForMaskedLM.from_pretrained("mrm8488/codeBERTaJS", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from mrm8488/codeBERTaJS: direct link, hf CLI and curl.
- Browser
- Download file 336 MB
-
https://huggingface.co/mrm8488/codeBERTaJS/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://mrm8488/codeBERTaJS@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/mrm8488/codeBERTaJS/resolve/refs%2Fpr%2F1/model.safetensors
336 MB
- Xet hash:
- 71cd4a168d8e254307bd18453a032a61a08f1e1fb57c06987b4d197dc797edf3
- Size of remote file:
- 336 MB
- SHA256:
- 7396612a218caa906121bab6e6015668ff9530ee27219735206e544ac4d61ef8
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