Instructions to use harry85/LLAMA3-finetuned-own-data with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use harry85/LLAMA3-finetuned-own-data with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/llama-3-8b-bnb-4bit") model = PeftModel.from_pretrained(base_model, "harry85/LLAMA3-finetuned-own-data") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from harry85/LLAMA3-finetuned-own-data: direct link, hf CLI and curl.
- Browser
- Download file 9.09 MB
-
https://huggingface.co/harry85/LLAMA3-finetuned-own-data/resolve/main/tokenizer.json
- Command line
-
hf download hf://harry85/LLAMA3-finetuned-own-data/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/harry85/LLAMA3-finetuned-own-data/resolve/main/tokenizer.json
9.09 MB
File too large to display, you can check the raw version instead.