PEFT
Safetensors
Balinese
Indonesian
balinese
assistant
instruction-tuned
lora
gemma
low-resource
unsloth
checkpoint
experimental
Instructions to use timothydillan/gemma4-e2b-balinese-assistant with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use timothydillan/gemma4-e2b-balinese-assistant with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("timothydillan/gemma4-e2b-balinese-cpt") model = PeftModel.from_pretrained(base_model, "timothydillan/gemma4-e2b-balinese-assistant") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download adapter_model.safetensors from timothydillan/gemma4-e2b-balinese-assistant: direct link, hf CLI and curl.
- Browser
- Download file 101 MB
-
https://huggingface.co/timothydillan/gemma4-e2b-balinese-assistant/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://timothydillan/gemma4-e2b-balinese-assistant/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/timothydillan/gemma4-e2b-balinese-assistant/resolve/main/adapter_model.safetensors
101 MB
- Xet hash:
- c3ebf2514e83fcf26e04cab8bd058174ac02ccd6035b4ead7c9ffab0da9fff43
- Size of remote file:
- 101 MB
- SHA256:
- 61c8943817852db8af5cc8b9954af62626ac49a0c389f51119c1a4c962b9fa06
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