Instructions to use wesley7137/codebertDM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wesley7137/codebertDM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="wesley7137/codebertDM")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("wesley7137/codebertDM") model = AutoModel.from_pretrained("wesley7137/codebertDM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from wesley7137/codebertDM: direct link, hf CLI and curl.
- Browser
- Download file 998 MB
-
https://huggingface.co/wesley7137/codebertDM/resolve/87ac0e69abf90e211d2494e79751d5cc5c3b5efc/optimizer.pt
- Command line
-
hf download hf://wesley7137/codebertDM@87ac0e69abf90e211d2494e79751d5cc5c3b5efc/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/wesley7137/codebertDM/resolve/87ac0e69abf90e211d2494e79751d5cc5c3b5efc/optimizer.pt
998 MB
- Xet hash:
- 753feba3e1cf5142699b48f455bf5667b4b201d4c4795f991d64b24a22b16de2
- Size of remote file:
- 998 MB
- SHA256:
- 0af66b07fe465a2b975e07f000c756dccdea087c30c3e5c875b4c1ad418d8ce4
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