Blip Image Captioning Base Bf16

🚀 Blip Image Captioning Base BF16

This is a quantized version of the image-to-text model Salesforce/blip-image-captioning-base. It reduces the model's memory size by 50% by quantizing the precision from float32 to bfloat16, changing the memory footprint from 989 MBs to 494 MBs.

🚀 Quick Start

Use the code below to get started with the model.

from transformers import BlipForConditionalGeneration, BlipProcessor
import requests
from PIL import Image

model = BlipForConditionalGeneration.from_pretrained("gospacedev/blip-image-captioning-base-bf16")
processor = BlipProcessor.from_pretrained("gospacedev/blip-image-captioning-base-bf16")

# Load sample image
image = Image.open(requests.get(img_url, stream=True).raw).convert('RGB')

# Generate output
inputs = processor(image, return_tensors="pt")
output = model.generate(**inputs)
result = processor.decode(out[0], skip_special_tokens=True)

print(results)

✨ Features

Example

a cat sitting on top of a purple and red striped carpet

📚 Documentation

Model Details

📄 License

This model is licensed under the MIT License.