Instructions to use AllenGeng/CodeBert15 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AllenGeng/CodeBert15 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="AllenGeng/CodeBert15")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("AllenGeng/CodeBert15") model = AutoModelForTokenClassification.from_pretrained("AllenGeng/CodeBert15", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from AllenGeng/CodeBert15: direct link, hf CLI and curl.
- Browser
- Download file 496 MB
-
https://huggingface.co/AllenGeng/CodeBert15/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://AllenGeng/CodeBert15@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/AllenGeng/CodeBert15/resolve/refs%2Fpr%2F1/pytorch_model.bin
496 MB
- Xet hash:
- 24e4854aabf94940b202c2976997d50fa6eb7a1fe938e67508f26b70ce5ced53
- Size of remote file:
- 496 MB
- SHA256:
- 514199754cd36fae1d4add4a7e245b50802b715b508bc76ab73c7166e2022e1e
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