Instructions to use buelfhood/GraphCodeBERT_BCB_ChaFT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use buelfhood/GraphCodeBERT_BCB_ChaFT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="buelfhood/GraphCodeBERT_BCB_ChaFT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("buelfhood/GraphCodeBERT_BCB_ChaFT") model = AutoModelForSequenceClassification.from_pretrained("buelfhood/GraphCodeBERT_BCB_ChaFT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from buelfhood/GraphCodeBERT_BCB_ChaFT: direct link, hf CLI and curl.
- Browser
- Download file 243 Bytes
-
https://huggingface.co/buelfhood/GraphCodeBERT_BCB_ChaFT/resolve/main/optimizer.pt
- Command line
-
hf download hf://buelfhood/GraphCodeBERT_BCB_ChaFT/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/buelfhood/GraphCodeBERT_BCB_ChaFT/resolve/main/optimizer.pt
243 Bytes
- Xet hash:
- 63137e0c7ee11c094f470e2296ecc0f6fd1c911e0e51c2d9ad99e4d395bc63a4
- Size of remote file:
- 243 Bytes
- SHA256:
- 42919e916e167cb8f9a7aea817cc24c5bc27462e91ea1612ca2ae0244690c088
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