Feature Extraction
Transformers
PyTorch
roberta
code-understanding
unixcoder
text-embeddings-inference
Instructions to use Henry65/RepoSim4Py with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Henry65/RepoSim4Py with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Henry65/RepoSim4Py")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Henry65/RepoSim4Py") model = AutoModel.from_pretrained("Henry65/RepoSim4Py", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download .gitattributes from Henry65/RepoSim4Py: direct link, hf CLI and curl.
- Browser
- Download file 108 Bytes
-
https://huggingface.co/Henry65/RepoSim4Py/resolve/refs%2Fpr%2F1/.gitattributes
- Command line
-
hf download hf://Henry65/RepoSim4Py@refs/pr/1/.gitattributes
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curl -L -o .gitattributes https://huggingface.co/Henry65/RepoSim4Py/resolve/refs%2Fpr%2F1/.gitattributes
108 Bytes
| pytorch_model.bin filter=lfs diff=lfs merge=lfs -text | |
| model.safetensors filter=lfs diff=lfs merge=lfs -text | |