Instructions to use mehmetdavut/ruby3.4-llama-3.2-3b-1k-hq-16bit-gemini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mehmetdavut/ruby3.4-llama-3.2-3b-1k-hq-16bit-gemini with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.2-3B-Instruct") model = PeftModel.from_pretrained(base_model, "mehmetdavut/ruby3.4-llama-3.2-3b-1k-hq-16bit-gemini") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from mehmetdavut/ruby3.4-llama-3.2-3b-1k-hq-16bit-gemini: direct link, hf CLI and curl.
- Browser
- Download file 97.3 MB
-
https://huggingface.co/mehmetdavut/ruby3.4-llama-3.2-3b-1k-hq-16bit-gemini/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://mehmetdavut/ruby3.4-llama-3.2-3b-1k-hq-16bit-gemini/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/mehmetdavut/ruby3.4-llama-3.2-3b-1k-hq-16bit-gemini/resolve/main/adapter_model.safetensors
97.3 MB
- Xet hash:
- 1841b400a91d64c98e0168e0d3615383f147fea42765b166c607d189cc3a51ab
- Size of remote file:
- 97.3 MB
- SHA256:
- a4f22a3797a0c17cc87ecfc0b4d02be8aea7b9155488954172a5f6c44c3fd7c2
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