Instructions to use RTannous/llama3.2-vision-instruct-adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use RTannous/llama3.2-vision-instruct-adapter with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/llama-3.2-11b-vision-instruct-unsloth-bnb-4bit") model = PeftModel.from_pretrained(base_model, "RTannous/llama3.2-vision-instruct-adapter") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from RTannous/llama3.2-vision-instruct-adapter: direct link, hf CLI and curl.
- Browser
- Download file 17.2 MB
-
https://huggingface.co/RTannous/llama3.2-vision-instruct-adapter/resolve/main/tokenizer.json
- Command line
-
hf download hf://RTannous/llama3.2-vision-instruct-adapter/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/RTannous/llama3.2-vision-instruct-adapter/resolve/main/tokenizer.json
17.2 MB
- Xet hash:
- bd7eb1d9df05e290be5ba369901a43352fc5e881abdc4a687ee98106e9724ea8
- Size of remote file:
- 17.2 MB
- SHA256:
- d34b8b90d18ab7ffd5282840a84d5d4df705e2c8e6f74c906ee0a1ea5b6bd9dd
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