Instructions to use ShimbaLLM/Dupe-R-IMG with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ShimbaLLM/Dupe-R-IMG with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ShimbaLLM/Dupe-R-IMG", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model_final_ema.pt from ShimbaLLM/Dupe-R-IMG: direct link, hf CLI and curl.
- Browser
- Download file 417 MB
-
https://huggingface.co/ShimbaLLM/Dupe-R-IMG/resolve/main/model_final_ema.pt
- Command line
-
hf download hf://ShimbaLLM/Dupe-R-IMG/model_final_ema.pt
-
curl -L -o model_final_ema.pt https://huggingface.co/ShimbaLLM/Dupe-R-IMG/resolve/main/model_final_ema.pt
417 MB
- Xet hash:
- 00cd10ff2984d0f2036d8e0f36a9ee5fdf2292f4ac2865ce0dca950eeb115f92
- Size of remote file:
- 417 MB
- SHA256:
- e96aa0537e0fd120af82b3a606dd50c90ae079ac7aa97b38a8da4882daeeee48
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