Instructions to use dusersad12/SkylineLM-ReleaseRepo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dusersad12/SkylineLM-ReleaseRepo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="dusersad12/SkylineLM-ReleaseRepo")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("dusersad12/SkylineLM-ReleaseRepo") model = AutoModel.from_pretrained("dusersad12/SkylineLM-ReleaseRepo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from dusersad12/SkylineLM-ReleaseRepo: direct link, hf CLI and curl.
- Browser
- Download file 52 Bytes
-
https://huggingface.co/dusersad12/SkylineLM-ReleaseRepo/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://dusersad12/SkylineLM-ReleaseRepo/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/dusersad12/SkylineLM-ReleaseRepo/resolve/main/pytorch_model.bin
52 Bytes
- Xet hash:
- 33daf85b9e53bc6efd751dd879c5603af806459d2d1ff751011053b1f4fb1d03
- Size of remote file:
- 52 Bytes
- SHA256:
- c81ae88e9820f5375638af52a80cacda5feffb9112e5e29781a2d9ca2efb1fd6
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