Instructions to use Cherran/sample_model_llama3.2_sft_dpo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Cherran/sample_model_llama3.2_sft_dpo with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/llama-3.2-3b-instruct-bnb-4bit") model = PeftModel.from_pretrained(base_model, "Cherran/sample_model_llama3.2_sft_dpo") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Cherran/sample_model_llama3.2_sft_dpo: direct link, hf CLI and curl.
- Browser
- Download file 9.09 MB
-
https://huggingface.co/Cherran/sample_model_llama3.2_sft_dpo/resolve/main/tokenizer.json
- Command line
-
hf download hf://Cherran/sample_model_llama3.2_sft_dpo/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Cherran/sample_model_llama3.2_sft_dpo/resolve/main/tokenizer.json
9.09 MB
File too large to display, you can check the raw version instead.