Instructions to use nuojohnchen/zephyr-7b-sft-qlora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nuojohnchen/zephyr-7b-sft-qlora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/mntcephfs/data/med/guimingchen/models/general/Mistral-7B-Instruct-v0.1") model = PeftModel.from_pretrained(base_model, "nuojohnchen/zephyr-7b-sft-qlora") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from nuojohnchen/zephyr-7b-sft-qlora: direct link, hf CLI and curl.
- Browser
- Download file 5.88 kB
-
https://huggingface.co/nuojohnchen/zephyr-7b-sft-qlora/resolve/main/training_args.bin
- Command line
-
hf download hf://nuojohnchen/zephyr-7b-sft-qlora/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/nuojohnchen/zephyr-7b-sft-qlora/resolve/main/training_args.bin
5.88 kB
- Xet hash:
- c98d2c60d2eda7e351b7229fd4e55d8d7ebe91151c242e761848c3dc05587c70
- Size of remote file:
- 5.88 kB
- SHA256:
- bf8e0b74056b6aca43c9a309076f6041c733efdb40357317c9500bf9923b5368
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