Instructions to use wwookk/graphcodebert_slice with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wwookk/graphcodebert_slice with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wwookk/graphcodebert_slice")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wwookk/graphcodebert_slice") model = AutoModelForSequenceClassification.from_pretrained("wwookk/graphcodebert_slice", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from wwookk/graphcodebert_slice: direct link, hf CLI and curl.
- Browser
- Download file 5.05 kB
-
https://huggingface.co/wwookk/graphcodebert_slice/resolve/3436b63c10393c79dccb730115a3879defa85a1e/training_args.bin
- Command line
-
hf download hf://wwookk/graphcodebert_slice@3436b63c10393c79dccb730115a3879defa85a1e/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/wwookk/graphcodebert_slice/resolve/3436b63c10393c79dccb730115a3879defa85a1e/training_args.bin
5.05 kB
- Xet hash:
- f3d18779056e2e05be1fe7c7a5643a4a89c35b39c00089be02f8c3f24fe5c60e
- Size of remote file:
- 5.05 kB
- SHA256:
- b706edcdb160f972a9e03c8ec87a73fc907817dc44bc26ccfe27e593a76b0ac6
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