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Model: typhoon-ai/typhoon2-qwen2vl-7b-vision-instruct Source: Original Platform
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---
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inference: false
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language:
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- th
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- en
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library_name: transformers
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license: apache-2.0
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pipeline_tag: text-generation
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base_model:
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- Qwen/Qwen2-VL-7B-Instruct
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---
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# **Typhoon2-Vision**
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**Typhoon2-qwen2vl-7b-vision-instruct** is a Thai 🇹🇭 vision-language model designed to support both image and video inputs. While Qwen2-VL is built to handle both image and video processing tasks, Typhoon2-VL is specifically optimized for image-based applications.
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For technical-report. please see our [arxiv](https://arxiv.org/abs/2412.13702).
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# **Model Description**
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Here we provide **Typhoon2-qwen2vl-7b-vision-instruct** which is built upon [Qwen2-VL-7B-Instruct](https://huggingface.co/Qwen/Qwen2-VL-7B-Instruct).
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- **Model type**: A 7B instruct decoder-only model with vision encoder based on Qwen2 architecture.
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- **Requirement**: transformers 4.38.0 or newer.
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- **Primary Language(s)**: Thai 🇹🇭 and English 🇬🇧
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- **Demo:**: [https://vision.opentyphoon.ai/](https://vision.opentyphoon.ai/)
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- **License**: Apache-2.0
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# **Quickstart**
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Here we show a code snippet to show you how to use the model with transformers.
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Before running the snippet, you need to install the following dependencies:
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```shell
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pip install torch transformers accelerate pillow
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```
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## How to Get Started with the Model
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Use the code below to get started with the model.
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<p align="center">
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<img src="https://cdn.pixabay.com/photo/2023/05/16/09/15/bangkok-7997046_1280.jpg" width="80%"/>
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<p>
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**Question:** ระบุชื่อสถานที่และประเทศของภาพนี้เป็นภาษาไทย
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**Answer:** พระบรมมหาราชวัง, กรุงเทพฯ, ประเทศไทย
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```python
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from PIL import Image
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import requests
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from transformers import Qwen2VLForConditionalGeneration, AutoProcessor
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model_name = "scb10x/typhoon2-qwen2vl-7b-vision-instruct"
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model = Qwen2VLForConditionalGeneration.from_pretrained(
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model_name, torch_dtype="auto", device_map="auto"
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)
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processor = AutoProcessor.from_pretrained(model_name)
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# Image
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url = "https://cdn.pixabay.com/photo/2023/05/16/09/15/bangkok-7997046_1280.jpg"
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image = Image.open(requests.get(url, stream=True).raw)
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conversation = [
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{
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"role": "user",
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"content": [
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{
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"type": "image",
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},
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{"type": "text", "text": "ระบุชื่อสถานที่และประเทศของภาพนี้เป็นภาษาไทย"},
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],
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}
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]
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# Preprocess the inputs
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text_prompt = processor.apply_chat_template(conversation, add_generation_prompt=True)
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inputs = processor(
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text=[text_prompt], images=[image], padding=True, return_tensors="pt"
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)
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inputs = inputs.to("cuda")
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output_ids = model.generate(**inputs, max_new_tokens=128)
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generated_ids = [
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output_ids[len(input_ids) :]
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for input_ids, output_ids in zip(inputs.input_ids, output_ids)
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]
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output_text = processor.batch_decode(
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generated_ids, skip_special_tokens=True, clean_up_tokenization_spaces=True
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)
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print(output_text)
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# ['พระบรมมหาราชวัง, กรุงเทพฯ, ประเทศไทย']
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```
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### Processing Multiple Images
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```python
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from PIL import Image
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import requests
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from transformers import Qwen2VLForConditionalGeneration, AutoProcessor
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model_name = "scb10x/typhoon2-qwen2vl-7b-vision-instruct"
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model = Qwen2VLForConditionalGeneration.from_pretrained(
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model_name, torch_dtype="auto", device_map="auto"
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)
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processor = AutoProcessor.from_pretrained(model_name)
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# Messages containing multiple images and a text query
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conversation = [
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{
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"role": "user",
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"content": [
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{
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"type": "image",
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},
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{
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"type": "image",
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},
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{"type": "text", "text": "ระบุ 3 สิ่งที่คล้ายกันในสองภาพนี้"},
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],
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}
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]
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urls = [
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"https://cdn.pixabay.com/photo/2023/05/16/09/15/bangkok-7997046_1280.jpg",
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"https://cdn.pixabay.com/photo/2020/08/10/10/09/bangkok-5477405_1280.jpg",
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]
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images = [Image.open(requests.get(url, stream=True).raw) for url in urls]
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# Preprocess the inputs
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text_prompt = processor.apply_chat_template(conversation, add_generation_prompt=True)
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inputs = processor(text=[text_prompt], images=images, padding=True, return_tensors="pt")
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inputs = inputs.to("cuda")
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# Inference
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generated_ids = model.generate(**inputs, max_new_tokens=128)
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generated_ids_trimmed = [
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out_ids[len(in_ids) :] for in_ids, out_ids in zip(inputs.input_ids, generated_ids)
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]
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output_text = processor.batch_decode(
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generated_ids_trimmed, skip_special_tokens=True, clean_up_tokenization_spaces=False
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)
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print(output_text)
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# ['1. ทั้งสองภาพแสดงสถาปัตยกรรมที่มีลักษณะคล้ายกัน\n2. ทั้งสองภาพมีสีสันที่สวยงาม\n3. ทั้งสองภาพมีทิวทัศน์ที่สวยงาม']
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```
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### Tips
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To balance between performance of the model and the cost of computation, you can set minimum and maximum number of pixels by passing arguments to the processer.
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```python
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min_pixels = 128 * 28 * 28
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max_pixels = 2560 * 28 * 28
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processor = AutoProcessor.from_pretrained(
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model_name, min_pixels=min_pixels, max_pixels=max_pixels
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)
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```
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### Evaluation (Image)
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| Benchmark | **Llama-3.2-11B-Vision-Instruct** | **Qwen2-VL-7B-Instruct** | **Pathumma-llm-vision-1.0.0** | **Typhoon2-qwen2vl-7b-vision-instruct** |
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|-------------------------------------------|-----------------|---------------|---------------|------------------------|
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| **OCRBench** [Liu et al., 2024c](#) | **72.84** / 51.10 | 72.31 / **57.90** | 32.74 / 25.87 | 64.38 / 49.60 |
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| **MMBench (Dev)** [Liu et al., 2024b](#) | 76.54 / - | **84.10** / - | 19.51 / - | 83.66 / - |
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| **ChartQA** [Masry et al., 2022](#) | 13.41 / x | 47.45 / 45.00 | 64.20 / 57.83 | **75.71** / **72.56** |
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| **TextVQA** [Singh et al., 2019](#) | 32.82 / x | 91.40 / 88.70 | 32.54 / 28.84 | **91.45** / **88.97** |
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| **OCR (TH)** [OpenThaiGPT, 2024](#) | **64.41** / 35.58 | 56.47 / 55.34 | 6.38 / 2.88 | 64.24 / **63.11** |
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| **M3Exam Images (TH)** [Zhang et al., 2023c](#) | 25.46 / - | 32.17 / - | 29.01 / - | **33.67** / - |
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| **GQA (TH)** [Hudson et al., 2019](#) | 31.33 / - | 34.55 / - | 10.20 / - | **50.25** / - |
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| **MTVQ (TH)** [Tang et al., 2024b](#) | 11.21 / 4.31 | 23.39 / 13.79 | 7.63 / 1.72 | **30.59** / **21.55** |
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| **Average** | 37.67 / x | 54.26 / 53.85 | 25.61 / 23.67 | **62.77** / **59.02** |
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Note: The first value in each cell represents **Rouge-L**.The second value (after `/`) represents **Accuracy**, normalized such that **Rouge-L = 100%**.
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## **Intended Uses & Limitations**
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This model is an instructional model. However, it’s still undergoing development. It incorporates some level of guardrails, but it still may produce answers that are inaccurate, biased, or otherwise objectionable in response to user prompts. We recommend that developers assess these risks in the context of their use case.
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## **Follow us**
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**https://twitter.com/opentyphoon**
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## **Support**
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**https://discord.gg/us5gAYmrxw**
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## **Citation**
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- If you find Typhoon2 useful for your work, please cite it using:
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```
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@misc{typhoon2,
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title={Typhoon 2: A Family of Open Text and Multimodal Thai Large Language Models},
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author={Kunat Pipatanakul and Potsawee Manakul and Natapong Nitarach and Warit Sirichotedumrong and Surapon Nonesung and Teetouch Jaknamon and Parinthapat Pengpun and Pittawat Taveekitworachai and Adisai Na-Thalang and Sittipong Sripaisarnmongkol and Krisanapong Jirayoot and Kasima Tharnpipitchai},
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year={2024},
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eprint={2412.13702},
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archivePrefix={arXiv},
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primaryClass={cs.CL},
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url={https://arxiv.org/abs/2412.13702},
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}
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```
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{
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"chat_template": "{% set image_count = namespace(value=0) %}{% set video_count = namespace(value=0) %}{% for message in messages %}{% if loop.first and message['role'] != 'system' %}<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n{% endif %}<|im_start|>{{ message['role'] }}\n{% if message['content'] is string %}{{ message['content'] }}<|im_end|>\n{% else %}{% for content in message['content'] %}{% if content['type'] == 'image' or 'image' in content or 'image_url' in content %}{% set image_count.value = image_count.value + 1 %}{% if add_vision_id %}Picture {{ image_count.value }}: {% endif %}<|vision_start|><|image_pad|><|vision_end|>{% elif content['type'] == 'video' or 'video' in content %}{% set video_count.value = video_count.value + 1 %}{% if add_vision_id %}Video {{ video_count.value }}: {% endif %}<|vision_start|><|video_pad|><|vision_end|>{% elif 'text' in content %}{{ content['text'] }}{% endif %}{% endfor %}<|im_end|>\n{% endif %}{% endfor %}{% if add_generation_prompt %}<|im_start|>assistant\n{% endif %}"
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}
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config.json
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config.json
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{
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"_name_or_path": "Qwen/Qwen2-VL-7B-Instruct",
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"architectures": [
|
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"Qwen2VLForConditionalGeneration"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 151643,
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"hidden_act": "silu",
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"hidden_size": 3584,
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"initializer_range": 0.02,
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"intermediate_size": 18944,
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"max_position_embeddings": 32768,
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"max_window_layers": 28,
|
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"model_type": "qwen2_vl",
|
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"num_attention_heads": 28,
|
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"num_hidden_layers": 28,
|
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"num_key_value_heads": 4,
|
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"rms_norm_eps": 1e-06,
|
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"rope_scaling": {
|
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"mrope_section": [
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16,
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24,
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24
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],
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"rope_type": "default",
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"type": "default"
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},
|
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"rope_theta": 1000000.0,
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"sliding_window": 32768,
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"tie_word_embeddings": false,
|
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"torch_dtype": "bfloat16",
|
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"transformers_version": "4.46.1",
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"use_cache": true,
|
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"use_sliding_window": false,
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"video_token_id": 151656,
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"vision_config": {
|
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"in_chans": 3,
|
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"model_type": "qwen2_vl",
|
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"spatial_patch_size": 14
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},
|
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"vision_end_token_id": 151653,
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"vision_start_token_id": 151652,
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"vision_token_id": 151654,
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"vocab_size": 152064
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}
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generation_config.json
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{
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"bos_token_id": 151643,
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"do_sample": true,
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"eos_token_id": [
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],
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"pad_token_id": 151643,
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"temperature": 0.01,
|
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"top_k": 1,
|
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"top_p": 0.001,
|
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"transformers_version": "4.46.1"
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}
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|
||||
}
|
||||
}
|
||||
29
preprocessor_config.json
Normal file
29
preprocessor_config.json
Normal file
@@ -0,0 +1,29 @@
|
||||
{
|
||||
"do_convert_rgb": true,
|
||||
"do_normalize": true,
|
||||
"do_rescale": true,
|
||||
"do_resize": true,
|
||||
"image_mean": [
|
||||
0.48145466,
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0.4578275,
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0.40821073
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],
|
||||
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0.26862954,
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0.26130258,
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0.27577711
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|
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||||
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|
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||||
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||||
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|
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"min_pixels": 3136
|
||||
},
|
||||
"temporal_patch_size": 2
|
||||
}
|
||||
31
special_tokens_map.json
Normal file
31
special_tokens_map.json
Normal file
@@ -0,0 +1,31 @@
|
||||
{
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>",
|
||||
"<|object_ref_start|>",
|
||||
"<|object_ref_end|>",
|
||||
"<|box_start|>",
|
||||
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|
||||
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|
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|
||||
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|
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|
||||
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|
||||
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|
||||
"<|video_pad|>"
|
||||
],
|
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|
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|
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|
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"single_word": false
|
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},
|
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|
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|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:091aa7594dc2fcfbfa06b9e3c22a5f0562ac14f30375c13af7309407a0e67b8a
|
||||
size 11420371
|
||||
144
tokenizer_config.json
Normal file
144
tokenizer_config.json
Normal file
@@ -0,0 +1,144 @@
|
||||
{
|
||||
"add_prefix_space": false,
|
||||
"added_tokens_decoder": {
|
||||
"151643": {
|
||||
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|
||||
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|
||||
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|
||||
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|
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"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151644": {
|
||||
"content": "<|im_start|>",
|
||||
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|
||||
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|
||||
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|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151645": {
|
||||
"content": "<|im_end|>",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"special": true
|
||||
},
|
||||
"151646": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
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|
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|
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|
||||
},
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
"151649": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"special": true
|
||||
},
|
||||
"151650": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
"151651": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
"151653": {
|
||||
"content": "<|vision_end|>",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
"151654": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
"151655": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
"151656": {
|
||||
"content": "<|video_pad|>",
|
||||
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|
||||
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|
||||
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|
||||
"single_word": false,
|
||||
"special": true
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>",
|
||||
"<|object_ref_start|>",
|
||||
"<|object_ref_end|>",
|
||||
"<|box_start|>",
|
||||
"<|box_end|>",
|
||||
"<|quad_start|>",
|
||||
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|
||||
"<|vision_start|>",
|
||||
"<|vision_end|>",
|
||||
"<|vision_pad|>",
|
||||
"<|image_pad|>",
|
||||
"<|video_pad|>"
|
||||
],
|
||||
"bos_token": null,
|
||||
"chat_template": "{% set image_count = namespace(value=0) %}{% set video_count = namespace(value=0) %}{% for message in messages %}{% if loop.first and message['role'] != 'system' %}<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n{% endif %}<|im_start|>{{ message['role'] }}\n{% if message['content'] is string %}{{ message['content'] }}<|im_end|>\n{% else %}{% for content in message['content'] %}{% if content['type'] == 'image' or 'image' in content or 'image_url' in content %}{% set image_count.value = image_count.value + 1 %}{% if add_vision_id %}Picture {{ image_count.value }}: {% endif %}<|vision_start|><|image_pad|><|vision_end|>{% elif content['type'] == 'video' or 'video' in content %}{% set video_count.value = video_count.value + 1 %}{% if add_vision_id %}Video {{ video_count.value }}: {% endif %}<|vision_start|><|video_pad|><|vision_end|>{% elif 'text' in content %}{{ content['text'] }}{% endif %}{% endfor %}<|im_end|>\n{% endif %}{% endfor %}{% if add_generation_prompt %}<|im_start|>assistant\n{% endif %}",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"errors": "replace",
|
||||
"model_max_length": 32768,
|
||||
"pad_token": "<|endoftext|>",
|
||||
"padding_side": "left",
|
||||
"processor_class": "Qwen2VLProcessor",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null
|
||||
}
|
||||
1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user