Instructions to use Binu30/gemma_3_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Binu30/gemma_3_lora with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Binu30/gemma_3_lora", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download tokenizer.json from Binu30/gemma_3_lora: direct link, hf CLI and curl.
- Browser
- Download file 33.4 MB
-
https://huggingface.co/Binu30/gemma_3_lora/resolve/main/tokenizer.json
- Command line
-
hf download hf://Binu30/gemma_3_lora/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Binu30/gemma_3_lora/resolve/main/tokenizer.json
33.4 MB
- Xet hash:
- 2fda4185effc006ad7504d1869da5d95f7bc74b33c65df706a91d646fcea81c5
- Size of remote file:
- 33.4 MB
- SHA256:
- d6c55cea4686e2b3756b2c556fbb27a4b14a925e79119cdaf70acdce26147690
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