Instructions to use barca-boy/lora_model_gemma-3-4b-it_anushtup_final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use barca-boy/lora_model_gemma-3-4b-it_anushtup_final with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("barca-boy/lora_model_gemma-3-4b-it_anushtup_final", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download adapter_model.safetensors from barca-boy/lora_model_gemma-3-4b-it_anushtup_final: direct link, hf CLI and curl.
- Browser
- Download file 131 MB
-
https://huggingface.co/barca-boy/lora_model_gemma-3-4b-it_anushtup_final/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://barca-boy/lora_model_gemma-3-4b-it_anushtup_final/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/barca-boy/lora_model_gemma-3-4b-it_anushtup_final/resolve/main/adapter_model.safetensors
131 MB
- Xet hash:
- eab1483752118ef6fa37b35290f167d02e4c4e84cec1f56757505016f1225be8
- Size of remote file:
- 131 MB
- SHA256:
- b895776dcc019baad2e4e3e101ea019f1b9bbd8f5ffe1825d70b0e421e97fdb5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.