llama3-vision-alpha

projection module trained to add vision capabilties to Llama 3 using SigLIP. built by @yeswondwerr and @qtnx_

usable directly in Transformers, warning: bitsandbytes quantization is currently not supported!

usage

pip install torch transformers pillow

import torch
from PIL import Image
from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "qresearch/llama-3-vision-alpha-hf"
model = AutoModelForCausalLM.from_pretrained(
    model_id, trust_remote_code=True, torch_dtype=torch.float16
).to("cuda")

tokenizer = AutoTokenizer.from_pretrained(
    model_id,
    use_fast=True,
)

image = Image.open("image_path")

print(
    tokenizer.decode(
        model.answer_question(image, "question", tokenizer),
        skip_special_tokens=True,
    )
)

examples

Image	Examples
	What is the title of this book? answer briefly The title of the book is "The Little Book of Deep Learning". Where is the person standing? answer briefly The person is standing on the balcony. Describe the image The image shows a person holding a book with a cityscape visible through the window behind them. The book has a cover with a title that reads "The Little Book of Deep Learning" in bold letters.
	What type of food is the girl holding? answer briefly A hamburger! What color is the woman's hair? answer briefly It's white! Describe the image The image is of a young girl with short, curly hair and a sweet smile, holding a giant hamburger in her hand. She's sitting at a table with a festive dinner setting, surrounded by candles and a warm glow. Her eyes are shining with excitement and contentment as she takes a big bite of the burger.

acknowledgements

• Liu et al. : LLaVA
• Moon et al. : AnyMAL
• vikhyatk : moondream, test images

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