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florence2-large-ft-gufeng_v3
F16/florence2-large-ft-gufeng_v3
florence2-large-ft-gufeng_v3 is a image-text-to-text model from F16. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for transformers.
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At a glance
- Task
- Image-Text-to-Text
- Library
- transformers
- Model type
- florence2
- Access
- Public
- Created
- Jul 8, 2024
- Updated
- Jul 28, 2024
- SHA
- e3abe693
Try a prompt
Model card
From the Hugging Face model README
How to Get Started with the Model
Use the code below to get started with the model.
import requests
from PIL import Image
from transformers import AutoProcessor, AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("F16/florence2-large-ft-gufeng_v3", trust_remote_code=True)
processor = AutoProcessor.from_pretrained("F16/florence2-large-ft-gufeng_v3", trust_remote_code=True)
prompt = "<MORE_DETAILED_CAPTION>"
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)
inputs = processor(text=prompt, images=image, return_tensors="pt")
generated_ids = model.generate(
input_ids=inputs["input_ids"],
pixel_values=inputs["pixel_values"],
max_new_tokens=1024,
do_sample=False,
num_beams=3
)
generated_text = processor.batch_decode(generated_ids, skip_special_tokens=False)[0]
parsed_answer = processor.post_process_generation(generated_text, task=prompt, image_size=(image.width, image.height))
print(parsed_answer)
license: mit
- Task
- Image-Text-to-Text
- Library
- transformers
- Type
- florence2
- Created
- Jul 8, 2024
- Updated
- Jul 28, 2024