初始化项目，由ModelHub XC社区提供模型

Model: NexaAIDev/Qwen3-VL-4B-Instruct-GGUF
Source: Original Platform

README.md

@@ -0,0 +1,48 @@
+---
+pipeline_tag: image-text-to-text
+base_model:
+- Qwen/Qwen3-VL-4B-Instruct
+---
+# Qwen3-VL-4B-Instruct
+
+Run **Qwen3-VL-4B-Instruct** optimized for CPU/GPU with [NexaSDK](https://github.com/NexaAI/nexa-sdk).
+
+## Quickstart
+
+1. **Install [NexaSDK](https://github.com/NexaAI/nexa-sdk)**
+2. Run the model locally with one line of code:
+
+   ```bash
+   nexa infer NexaAI/Qwen3-VL-4B-Instruct-GGUF
+   ```
+
+## Model Description
+**Qwen3-VL-4B-Instruct** is a 4-billion-parameter instruction-tuned multimodal large language model from Alibaba Cloud’s Qwen team.  
+As part of the **Qwen3-VL** series, it fuses powerful vision-language understanding with conversational fine-tuning, optimized for real-world applications such as chat-based reasoning, document analysis, and visual dialogue.
+
+The *Instruct* variant is tuned for following user prompts naturally and safely — producing concise, relevant, and user-aligned responses across text, image, and video contexts.
+
+## Features
+- **Instruction-Following**: Optimized for dialogue, explanation, and user-friendly task completion.  
+- **Vision-Language Fusion**: Understands and reasons across text, images, and video frames.  
+- **Multilingual Capability**: Handles multiple languages for diverse global use cases.  
+- **Contextual Coherence**: Balances reasoning ability with natural, grounded conversational tone.  
+- **Lightweight & Deployable**: 4B parameters make it efficient for edge and device-level inference.
+
+## Use Cases
+- Visual chatbots and assistants  
+- Image captioning and scene understanding  
+- Chart, document, or screenshot analysis  
+- Educational or tutoring systems with visual inputs  
+- Multilingual, multimodal question answering  
+
+## Inputs and Outputs
+**Input:**
+- Text prompts, image(s), or mixed multimodal instructions.  
+
+**Output:**
+- Natural-language responses or visual reasoning explanations.  
+- Can return structured text (summaries, captions, answers, etc.) depending on the prompt.
+
+## License
+Refer to the [official Qwen license](https://huggingface.co/Qwen) for terms of use and redistribution.