Instructions to use dusersad12/MyStellarModel-ProdRepo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dusersad12/MyStellarModel-ProdRepo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="dusersad12/MyStellarModel-ProdRepo")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("dusersad12/MyStellarModel-ProdRepo") model = AutoModel.from_pretrained("dusersad12/MyStellarModel-ProdRepo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from dusersad12/MyStellarModel-ProdRepo: direct link, hf CLI and curl.
- Browser
- Download file 33 Bytes
-
https://huggingface.co/dusersad12/MyStellarModel-ProdRepo/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://dusersad12/MyStellarModel-ProdRepo/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/dusersad12/MyStellarModel-ProdRepo/resolve/main/pytorch_model.bin
33 Bytes
- Xet hash:
- 4d39e49ff15e67ea88ab0b3c1474de392c3481d0e0172f9df88fe23c42c5798d
- Size of remote file:
- 33 Bytes
- SHA256:
- 74d5cee7eb50055ca91bae3c2c57322b3ddd157077a5310555a48cbed9280ee7
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