Instructions to use mehmetdavut/ruby3.4-llama-3.2-3b-5k-all-8bit-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-5k-all-8bit-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-5k-all-8bit-gemini") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from mehmetdavut/ruby3.4-llama-3.2-3b-5k-all-8bit-gemini: direct link, hf CLI and curl.
- Browser
- Download file 5.5 kB
-
https://huggingface.co/mehmetdavut/ruby3.4-llama-3.2-3b-5k-all-8bit-gemini/resolve/66371521f9f11f40025e66097e1bdc9bc5f0c63b/training_args.bin
- Command line
-
hf download hf://mehmetdavut/ruby3.4-llama-3.2-3b-5k-all-8bit-gemini@66371521f9f11f40025e66097e1bdc9bc5f0c63b/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/mehmetdavut/ruby3.4-llama-3.2-3b-5k-all-8bit-gemini/resolve/66371521f9f11f40025e66097e1bdc9bc5f0c63b/training_args.bin
5.5 kB
- Xet hash:
- 603f66a21b07cc60e0ec77eb1e00d386f910e9367c6517256e7392a6610b0088
- Size of remote file:
- 5.5 kB
- SHA256:
- edfcea955d1191f8eabd4070cffb1835adc9158614c2a41fec6618557201f574
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