Instructions to use microsoft/unixcoder-base-unimodal with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/unixcoder-base-unimodal with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="microsoft/unixcoder-base-unimodal")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("microsoft/unixcoder-base-unimodal") model = AutoModel.from_pretrained("microsoft/unixcoder-base-unimodal", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from microsoft/unixcoder-base-unimodal: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/microsoft/unixcoder-base-unimodal/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://microsoft/unixcoder-base-unimodal/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/microsoft/unixcoder-base-unimodal/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- a23309460989c185d638ed95cbd14d65e28a66e2ef56c19e4f91b87fcab98114
- Size of remote file:
- 499 MB
- SHA256:
- bb342a3ff16d651829a0cb08618fa45cee56fbe6b06d8a6bb99ecf67f7f067ec
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