Instructions to use mehmetdavut/ruby3.4-gemma-2-9b-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-gemma-2-9b-1k-hq-16bit-gemini with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-2-9b-it") model = PeftModel.from_pretrained(base_model, "mehmetdavut/ruby3.4-gemma-2-9b-1k-hq-16bit-gemini") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from mehmetdavut/ruby3.4-gemma-2-9b-1k-hq-16bit-gemini: direct link, hf CLI and curl.
- Browser
- Download file 216 MB
-
https://huggingface.co/mehmetdavut/ruby3.4-gemma-2-9b-1k-hq-16bit-gemini/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://mehmetdavut/ruby3.4-gemma-2-9b-1k-hq-16bit-gemini/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/mehmetdavut/ruby3.4-gemma-2-9b-1k-hq-16bit-gemini/resolve/main/adapter_model.safetensors
216 MB
- Xet hash:
- aa1a049cb3709200a80e1c3214478a2d1d31230cfed019e6e86c1b161455ccc8
- Size of remote file:
- 216 MB
- SHA256:
- f05d83c4b2ecc8273d7d3b2b74ac2ac80bf0c60e9f271e7c12520228d51c12c4
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