Instructions to use Rimyy/LLAmaFineTuneMathDataFormat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Rimyy/LLAmaFineTuneMathDataFormat with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Llama-2-7b-chat-hf") model = PeftModel.from_pretrained(base_model, "Rimyy/LLAmaFineTuneMathDataFormat") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from Rimyy/LLAmaFineTuneMathDataFormat: direct link, hf CLI and curl.
- Browser
- Download file 134 MB
-
https://huggingface.co/Rimyy/LLAmaFineTuneMathDataFormat/resolve/main/adapter_model.bin
- Command line
-
hf download hf://Rimyy/LLAmaFineTuneMathDataFormat/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/Rimyy/LLAmaFineTuneMathDataFormat/resolve/main/adapter_model.bin
134 MB
- Xet hash:
- 317d0eaf9c92d2fb4724caa78587e4983eccd57468492d9db12f8465c89b5435
- Size of remote file:
- 134 MB
- SHA256:
- 60ae14dbe49d98e48cc3f5363dea2662651edff36ee8abcade9ccd0ce16a32e1
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