karakuri vl 32b instruct 2507 EU AI Act Compliance Profile

KARAKURI VL 32B Instruct 2507

Model Details

Model Description

• Developed by: KARAKURI Inc.
• Model type: Vision-Language Models
• Languages: Japanese and English
• License: Apache 2.0
• Finetuned from model: Qwen/Qwen2.5-VL-32B-Instruct
• Contact: For questions and comments about the model, please email karakuri-rd@karakuri.ai
• Demo: https://vl.karakuri.cc/

Usage

Use in 🤗 Transformers

First, install the required dependencies:

pip install transformers accelerate qwen-vl-utils[decord]==0.0.8

Then, use the following code to load the model and generate responses:

from transformers import AutoModelForImageTextToText, AutoProcessor
from qwen_vl_utils import process_vision_info

model_name = "karakuri-ai/karakuri-vl-32b-instruct-2507"
model = AutoModelForImageTextToText.from_pretrained(
    model_name, torch_dtype="auto", device_map="auto"
)
processor = AutoProcessor.from_pretrained(model_name)

messages = [
    {
        "role": "user",
        "content": [
            {
                "type": "image",
                "image": "https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-VL/assets/demo.jpeg",
            },
            {"type": "text", "text": "Describe this image."},
        ],
    }
]

# Preparation for inference
text = processor.apply_chat_template(
    messages, tokenize=False, add_generation_prompt=True
)
image_inputs, video_inputs = process_vision_info(messages)
inputs = processor(
    text=[text],
    images=image_inputs,
    videos=video_inputs,
    padding=True,
    return_tensors="pt",
)
inputs = inputs.to(model.device)

# Inference: Generation of the output
generated_ids = model.generate(**inputs, max_new_tokens=128)
generated_ids_trimmed = [
    out_ids[len(in_ids) :] for in_ids, out_ids in zip(inputs.input_ids, generated_ids)
]
output_text = processor.bat

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Base Model