52 lines
2.4 KiB
Markdown
52 lines
2.4 KiB
Markdown
---
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pipeline_tag: image-text-to-text
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base_model:
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- Qwen/Qwen3-VL-8B-Instruct
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---
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# Qwen3-VL-8B-Instruct
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> [!NOTE]
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> Note currently only [NexaSDK](https://github.com/NexaAI/nexa-sdk) supports this model's GGUF.
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Run **Qwen3-VL-8B-Instruct** optimized for CPU/GPU with [NexaSDK](https://github.com/NexaAI/nexa-sdk).
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## Quickstart
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1. **Install [NexaSDK](https://github.com/NexaAI/nexa-sdk)**
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2. Run the model locally with one line of code:
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```bash
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nexa infer NexaAI/Qwen3-VL-8B-Instruct-GGUF
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```
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## Model Description
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**Qwen3-VL-8B-Instruct** is an 8-billion-parameter instruction-tuned multimodal large language model developed by the Qwen team at Alibaba Cloud.
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It belongs to the **Qwen3-VL** series, designed for seamless understanding and reasoning across text, image, and video. This version combines the visual intelligence of Qwen3-VL with the instruction-following capabilities of Qwen3-LM, enabling natural, grounded conversations around complex visual content.
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Compared to the 4B variant, the **8B** model delivers stronger reasoning, richer context retention, and improved performance on visual and multilingual benchmarks while maintaining efficiency for deployment.
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## Features
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- **Enhanced Visual Understanding**: Handles complex scenes, documents, and multi-image inputs.
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- **Instruction-Tuned Dialogue**: Produces coherent and context-aware responses aligned with user intent.
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- **Multilingual Support**: Capable of understanding and generating in multiple languages.
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- **Extended Context Window**: Supports longer text and multimodal contexts for better reasoning continuity.
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- **Optimized Performance**: Balances large-scale reasoning capability with deployability for high-end edge or server environments.
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## Use Cases
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- Visual chatbots and multimodal assistants
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- Document and chart interpretation
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- Image-grounded content generation and summarization
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- Video frame reasoning and analysis
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- Multilingual multimodal tutoring or knowledge assistants
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## Inputs and Outputs
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**Input:**
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- Text, images, or combined multimodal prompts
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- Optional video frames or sequential image sets
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**Output:**
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- Natural-language answers, summaries, captions, or structured reasoning outputs
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- Can provide visual explanations or reasoning narratives when prompted
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## License
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See the [official Qwen license](https://huggingface.co/Qwen) for details on usage and redistribution. |