update WhichModel enum
This commit is contained in:
jhqxxx
+35
-55
@@ -51,16 +51,16 @@ aha cli [OPTIONS] --model <MODEL>
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```bash
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# Download model and start service (default port 10100)
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aha cli -m qwen3vl-2b
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aha cli -m Qwen/Qwen3-VL-2B-Instruct
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# Specify port and save directory
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aha cli -m qwen3vl-2b -p 8080 --save-dir /data/models
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aha cli -m Qwen/Qwen3-VL-2B-Instruct -p 8080 --save-dir /data/models
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# Use local model (skip download)
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aha cli -m qwen3vl-2b --weight-path /path/to/model
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aha cli -m Qwen/Qwen3-VL-2B-Instruct --weight-path /path/to/model
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# Backward compatible way (equivalent to cli subcommand)
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aha -m qwen3vl-2b
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aha -m Qwen/Qwen3-VL-2B-Instruct
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# use gguf-path and mmproj-path
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aha cli -m qwen3.5-gguf --gguf-path /path/to/xxx.gguf --mmproj-path /path/to/mmproj-xxx.gguf
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@@ -89,34 +89,34 @@ aha run [OPTIONS] --model <MODEL> --input <INPUT> [--input <INPUT2>] [--weight-p
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```bash
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# VoxCPM1.5 text-to-speech (single input)
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aha run -m voxcpm1.5 -i "太阳当空照" -o output.wav --weight-path /path/to/model
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aha run -m OpenBMB/VoxCPM1.5 -i "太阳当空照" -o output.wav --weight-path /path/to/model
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# VoxCPM1.5 read input from file (single input)
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aha run -m voxcpm1.5 -i "file://./input.txt" --weight-path /path/to/model
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aha run -m OpenBMB/VoxCPM1.5 -i "file://./input.txt" --weight-path /path/to/model
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# MiniCPM4 text generation (single input)
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aha run -m minicpm4-0.5b -i "你好" --weight-path /path/to/model
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aha run -m OpenBMB/MiniCPM4-0.5B -i "你好" --weight-path /path/to/model
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# DeepSeek OCR image recognition (single input)
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aha run -m deepseek-ocr -i "image.jpg" --weight-path /path/to/model
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aha run -m deepseek-ai/DeepSeek-OCR -i "image.jpg" --weight-path /path/to/model
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# RMBG2.0 background removal (single input)
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aha run -m RMBG2.0 -i "photo.png" -o "no_bg.png" --weight-path /path/to/model
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aha run -m AI-ModelScope/RMBG-2.0 -i "photo.png" -o "no_bg.png" --weight-path /path/to/model
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# GLM-ASR speech recognition (two inputs: prompt text + audio file)
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aha run -m glm-asr-nano-2512 -i "请转写这段音频" -i "audio.wav" --weight-path /path/to/model
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aha run -m ZhipuAI/GLM-ASR-Nano-2512 -i "请转写这段音频" -i "audio.wav" --weight-path /path/to/model
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# Fun-ASR speech recognition (two inputs: prompt text + audio file)
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aha run -m fun-asr-nano-2512 -i "语音转写：" -i "audio.wav" --weight-path /path/to/model
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aha run -m FunAudioLLM/Fun-ASR-Nano-2512 -i "语音转写：" -i "audio.wav" --weight-path /path/to/model
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# qwen3 text generation (single input)
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aha run -m qwen3-0.6b -i "你好" --weight-path /path/to/model
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aha run -m Qwen/Qwen3-0.6B -i "你好" --weight-path /path/to/model
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# qwen2.5vl image understanding (two inputs: prompt text + image file)
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aha run -m qwen2.5vl-3b -i "请分析图片并提取所有可见文本内容，按从左到右、从上到下的布局，返回纯文本" -i "image.jpg" --weight-path /path/to/model
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aha run -m Qwen/Qwen2.5-VL-3B-Instruct -i "请分析图片并提取所有可见文本内容，按从左到右、从上到下的布局，返回纯文本" -i "image.jpg" --weight-path /path/to/model
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# Qwen3-ASR speech recognition (single input: audio file)
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aha run -m qwen3asr-0.6b -i "audio.wav" --weight-path /path/to/model
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aha run -m Qwen/Qwen3-ASR-0.6B -i "audio.wav" --weight-path /path/to/model
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# Qwen3.5-GGUF without mmproj (single input: prompt text)
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aha run -m qwen3.5-gguf -i 你如何看待AI --gguf-path /path/to/xxx.gguf
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@@ -152,19 +152,19 @@ aha serv [OPTIONS] --model <MODEL> [--weight-path <WEIGHT_PATH>] [--gguf-path <G
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```bash
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# Start service with default model path (~/.aha/{model_id})
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aha serv -m qwen3vl-2b
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aha serv -m Qwen/Qwen3-VL-2B-Instruct
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# Start service with local model
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aha serv -m qwen3vl-2b --weight-path /path/to/model
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aha serv -m Qwen/Qwen3-VL-2B-Instruct --weight-path /path/to/model
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# Start with specified port
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aha serv -m qwen3vl-2b -p 8080
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aha serv -m Qwen/Qwen3-VL-2B-Instruct -p 8080
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# Specify listen address
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aha serv -m qwen3vl-2b -a 0.0.0.0
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aha serv -m Qwen/Qwen3-VL-2B-Instruct -a 0.0.0.0
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# Enable remote shutdown (not recommended for production)
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aha serv -m qwen3vl-2b --allow-remote-shutdown
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aha serv -m Qwen/Qwen3-VL-2B-Instruct --allow-remote-shutdown
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```
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### ps - List running services
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@@ -229,16 +229,16 @@ aha download [OPTIONS] --model <MODEL>
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```bash
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# Download model to default directory
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aha download -m qwen3vl-2b
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aha download -m Qwen/Qwen3-VL-2B-Instruct
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# Specify save directory
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aha download -m qwen3vl-2b -s /data/models
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aha download -m Qwen/Qwen3-VL-2B-Instruct -s /data/models
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# Specify download retry count
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aha download -m qwen3vl-2b --download-retries 5
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aha download -m Qwen/Qwen3-VL-2B-Instruct --download-retries 5
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# Download MiniCPM4-0.5B model
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aha download -m minicpm4-0.5b -s models
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aha download -m OpenBMB/MiniCPM4-0.5B -s models
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```
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### delete - Delete downloaded model
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@@ -260,10 +260,10 @@ aha delete [OPTIONS] --model <MODEL>
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```bash
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# Delete RMBG2.0 model from default location
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aha delete -m rmbg2.0
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aha delete -m AI-ModelScope/RMBG-2.0
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# Delete Qwen3-VL-2B model
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aha delete --model qwen3vl-2b
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aha delete --model Qwen/Qwen3-VL-2B-Instruct
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```
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**Behavior:**
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@@ -311,12 +311,12 @@ Example:
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```json
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[
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{
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"name": "qwen3vl-2b",
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"name": "Qwen/Qwen3-VL-2B-Instruct",
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"model_id": "Qwen/Qwen3-VL-2B-Instruct",
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"type": "llm"
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},
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{
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"name": "deepseek-ocr",
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"name": "deepseek-ai/DeepSeek-OCR",
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"model_id": "deepseek-ai/DeepSeek-OCR",
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"type": "ocr"
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}
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@@ -328,27 +328,7 @@ Example:
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- `ocr`: Optical Character Recognition models
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- `asr`: Automatic Speech Recognition models
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- `image`: Image processing models
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## Supported Models
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| Model ID | Model Name | Description |
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|----------|------------|-------------|
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| `minicpm4-0.5b` | OpenBMB/MiniCPM4-0.5B | OpenBMB MiniCPM4 0.5B model |
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| `qwen2.5vl-3b` | Qwen/Qwen2.5-VL-3B-Instruct | Qwen 2.5 VL 3B model |
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| `qwen2.5vl-7b` | Qwen/Qwen2.5-VL-7B-Instruct | Qwen 2.5 VL 7B model |
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| `qwen3-0.6b` | Qwen/Qwen3-0.6B | Qwen 3 0.6B model |
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| `qwen3vl-2b` | Qwen/Qwen3-VL-2B-Instruct | Qwen 3 VL 2B model |
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| `qwen3vl-4b` | Qwen/Qwen3-VL-4B-Instruct | Qwen 3 VL 4B model |
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| `qwen3vl-8b` | Qwen/Qwen3-VL-8B-Instruct | Qwen 3 VL 8B model |
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| `qwen3vl-32b` | Qwen/Qwen3-VL-32B-Instruct | Qwen 3 VL 32B model |
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| `deepseek-ocr` | deepseek-ai/DeepSeek-OCR | DeepSeek OCR model |
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| `hunyuan-ocr` | Tencent-Hunyuan/HunyuanOCR | Tencent Hunyuan OCR model |
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| `paddleocr-vl` | PaddlePaddle/PaddleOCR-VL | Baidu PaddleOCR VL model |
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| `RMBG2.0` | AI-ModelScope/RMBG-2.0 | RMBG 2.0 background removal model |
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| `voxcpm` | OpenBMB/VoxCPM-0.5B | OpenBMB VoxCPM 0.5B speech synthesis model |
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| `voxcpm1.5` | OpenBMB/VoxCPM1.5 | OpenBMB VoxCPM 1.5 speech synthesis model |
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| `glm-asr-nano-2512` | ZhipuAI/GLM-ASR-Nano-2512 | Zhipu AI ASR Nano 2512 speech recognition model |
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| `fun-asr-nano-2512` | FunAudioLLM/Fun-ASR-Nano-2512 | FunAudioLLM ASR Nano 2512 speech recognition model |
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- `tts`： Text to speech
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## Common Use Cases
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@@ -356,31 +336,31 @@ Example:
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```bash
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# One command to download and start service
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aha -m qwen3vl-2b
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aha -m Qwen/Qwen3-VL-2B-Instruct
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```
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### Scenario 2: Start service with existing model
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```bash
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# Assuming model is downloaded to /data/models/Qwen/Qwen3-VL-2B-Instruct
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aha serv -m qwen3vl-2b --weight-path /data/models/Qwen/Qwen3-VL-2B-Instruct
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aha serv -m Qwen/Qwen3-VL-2B-Instruct --weight-path /data/models/Qwen/Qwen3-VL-2B-Instruct
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```
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### Scenario 3: Pre-download model
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```bash
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# Download model to specified directory for later use
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aha download -m qwen3vl-2b -s /data/models
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aha download -m Qwen/Qwen3-VL-2B-Instruct -s /data/models
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# Later start with local model
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aha serv -m qwen3vl-2b --weight-path /data/models/Qwen/Qwen3-VL-2B-Instruct
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aha serv -m Qwen/Qwen3-VL-2B-Instruct --weight-path /data/models/Qwen/Qwen3-VL-2B-Instruct
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```
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### Scenario 4: Custom service port and address
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```bash
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# Start service on 0.0.0.0:8080, allow external access
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aha -m qwen3vl-2b -a 0.0.0.0 -p 8080
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aha -m Qwen/Qwen3-VL-2B-Instruct -a 0.0.0.0 -p 8080
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```
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## API Endpoints
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@@ -421,10 +401,10 @@ To maintain compatibility with older versions, the following two usage methods a
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```bash
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# New way (recommended)
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aha cli -m qwen3vl-2b
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aha cli -m Qwen/Qwen3-VL-2B-Instruct
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# Old way (backward compatible)
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aha -m qwen3vl-2b
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aha -m Qwen/Qwen3-VL-2B-Instruct
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```
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## Notes
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