Paligemma Rich Captions

🚀 圖像文本轉文本模型

本項目是 PaliGemma 模型的微調版本，在 google/docci 數據集上進行訓練，生成的描述長度在 200 到 350 個字符之間。該模型的幻覺現象較少。

🚀 快速開始

安裝依賴

pip install git+https://github.com/huggingface/transformers

💻 使用示例

基礎用法

from transformers import AutoProcessor, PaliGemmaForConditionalGeneration
from PIL import Image
import requests
import torch

model_id = "gokaygokay/paligemma-rich-captions"

url = "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/tasks/car.jpg?download=true"
image = Image.open(requests.get(url, stream=True).raw)

model = PaliGemmaForConditionalGeneration.from_pretrained(model_id).to('cuda').eval()
processor = AutoProcessor.from_pretrained(model_id)

## prefix
prompt = "caption en"
model_inputs = processor(text=prompt, images=image, return_tensors="pt").to('cuda')
input_len = model_inputs["input_ids"].shape[-1]

with torch.inference_mode():
    generation = model.generate(**model_inputs, max_new_tokens=256, do_sample=False)
    generation = generation[0][input_len:]
    decoded = processor.decode(generation, skip_special_tokens=True)
    print(decoded)

📄 許可證

本項目採用 Apache-2.0 許可證。