Instructions to use renish1/medic_Llama3b_Instruct_4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use renish1/medic_Llama3b_Instruct_4bit with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/llama-3.2-3b-instruct-unsloth-bnb-4bit") model = PeftModel.from_pretrained(base_model, "renish1/medic_Llama3b_Instruct_4bit") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from renish1/medic_Llama3b_Instruct_4bit: direct link, hf CLI and curl.
- Browser
- Download file 5.56 kB
-
https://huggingface.co/renish1/medic_Llama3b_Instruct_4bit/resolve/main/training_args.bin
- Command line
-
hf download hf://renish1/medic_Llama3b_Instruct_4bit/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/renish1/medic_Llama3b_Instruct_4bit/resolve/main/training_args.bin
5.56 kB
- Xet hash:
- 8ede3a95acfda37766d1702657df37259197f90f6dcf61907a50c658d49f4926
- Size of remote file:
- 5.56 kB
- SHA256:
- e229c659430f7c50cd1de724e30fe1d376efdcb83a7b583364fc8c324a98f75c
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