Instructions to use Enoch/graphcodebert-py with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Enoch/graphcodebert-py with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Enoch/graphcodebert-py")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Enoch/graphcodebert-py") model = AutoModel.from_pretrained("Enoch/graphcodebert-py", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from Enoch/graphcodebert-py: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/Enoch/graphcodebert-py/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://Enoch/graphcodebert-py/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/Enoch/graphcodebert-py/resolve/main/flax_model.msgpack
499 MB
- Xet hash:
- ff8630b557dcfb21a3adcadbe720deff0174122a32282fc851e064660e473696
- Size of remote file:
- 499 MB
- SHA256:
- 2d7e6e6444bb0d55b4344b35be92ddd1812182e68ab76a1f4ae03fc166a6f2be
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