Instructions to use neulab/codebert-c with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use neulab/codebert-c with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="neulab/codebert-c")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("neulab/codebert-c") model = AutoModelForMaskedLM.from_pretrained("neulab/codebert-c", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from neulab/codebert-c: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/neulab/codebert-c/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://neulab/codebert-c@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/neulab/codebert-c/resolve/refs%2Fpr%2F1/pytorch_model.bin
499 MB
- Xet hash:
- fed9976be3f5a27ea42204c00553862303657e740570af491854ffe8fe6b30ba
- Size of remote file:
- 499 MB
- SHA256:
- 1cfe6e90696fd64cf8ce8aa42c43eccaee711697b82554e2d5f86a03aca952f2
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