Instructions to use AnalyticsIntelligence/PIDGIN_gemma3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnalyticsIntelligence/PIDGIN_gemma3 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("AnalyticsIntelligence/PIDGIN_gemma3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download adapter_model.safetensors from AnalyticsIntelligence/PIDGIN_gemma3: direct link, hf CLI and curl.
- Browser
- Download file 59.7 MB
-
https://huggingface.co/AnalyticsIntelligence/PIDGIN_gemma3/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://AnalyticsIntelligence/PIDGIN_gemma3/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/AnalyticsIntelligence/PIDGIN_gemma3/resolve/main/adapter_model.safetensors
59.7 MB
- Xet hash:
- b35a525747188ee74e51f25cb27ade934af683f41584de20f68ebad9367c342b
- Size of remote file:
- 59.7 MB
- SHA256:
- 7bc50eb3b65ca492962c0517fde1ed7bf0f094a3ca4887865ad107c4f41a65e1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.