Instructions to use hsatoliquid/gemma-product-description with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hsatoliquid/gemma-product-description with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("hsatoliquid/gemma-product-description", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from hsatoliquid/gemma-product-description: direct link, hf CLI and curl.
- Browser
- Download file 6.1 kB
-
https://huggingface.co/hsatoliquid/gemma-product-description/resolve/main/training_args.bin
- Command line
-
hf download hf://hsatoliquid/gemma-product-description/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/hsatoliquid/gemma-product-description/resolve/main/training_args.bin
6.1 kB
- Xet hash:
- 484cc5a164c686608f005a4fcd6269984847416f2e5e14bf28f1066d8bd8d727
- Size of remote file:
- 6.1 kB
- SHA256:
- 716c3752d2a69875c9e97e6a93c0af278ee76a8f3461aef2e79d233dd2e49d51
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