Instructions to use SamChen888/Gemma-RDE-Finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use SamChen888/Gemma-RDE-Finetuned with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-2-9b-it-bnb-4bit") model = PeftModel.from_pretrained(base_model, "SamChen888/Gemma-RDE-Finetuned") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download checkpoint-348/optimizer.pt from SamChen888/Gemma-RDE-Finetuned: direct link, hf CLI and curl.
- Browser
- Download file 217 MB
-
https://huggingface.co/SamChen888/Gemma-RDE-Finetuned/resolve/main/checkpoint-348/optimizer.pt
- Command line
-
hf download hf://SamChen888/Gemma-RDE-Finetuned/checkpoint-348/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/SamChen888/Gemma-RDE-Finetuned/resolve/main/checkpoint-348/optimizer.pt
217 MB
- Xet hash:
- 144addce230e137097edc6ee890e0e10a7f3443b3f9f6c3c24250a0db7a138c9
- Size of remote file:
- 217 MB
- SHA256:
- 8be51673193de7f2b5944aa880ab439633e74ed9a7bcb10e150c2f23087203bd
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