kosmos-2-patch14-224 EU AI Act Compliance Profile

Kosmos-2: Grounding Multimodal Large Language Models to the World

<a href="https://huggingface.co/microsoft/kosmos-2-patch14-224/resolve/main/annotated_snowman.jpg" target="_blank"><figure><img src="https://huggingface.co/microsoft/kosmos-2-patch14-224/resolve/main/annotated_snowman.jpg" width="384"><figcaption><b>[An image of a snowman warming himself by a fire.]</b></figcaption></figure></a>

This Hub repository contains a HuggingFace's transformers implementation of the original Kosmos-2 model from Microsoft.

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, AutoModelForVision2Seq


model = AutoModelForVision2Seq.from_pretrained("microsoft/kosmos-2-patch14-224")
processor = AutoProcessor.from_pretrained("microsoft/kosmos-2-patch14-224")

prompt = "<grounding>An image of"

url = "https://huggingface.co/microsoft/kosmos-2-patch14-224/resolve/main/snowman.png"
image = Image.open(requests.get(url, stream=True).raw)

# The original Kosmos-2 demo saves the image first then reload it. For some images, this will give slightly different image input and change the generation outputs.
image.save("new_image.jpg")
image = Image.open("new_image.jpg")

inputs = processor(text=prompt, images=image, return_tensors="pt")

generated_ids = model.generate(
    pixel_values=inputs["pixel_values"],
    input_ids=inputs["input_ids"],
    attention_mask=inputs["attention_mask"],
    image_embeds=None,
    image_embeds_position_mask=inputs["image_embeds_position_mask"],
    use_cache=True,
    max_new_tokens=128,
)
generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]

# Specify `cleanup_and_extract=False` in order to see the raw model generation.
processed_text = processor.post_process_generation(generated_text, cleanup_and_extract=False)

print(processed_text)
# `<gr

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