Instructions to use Qwen/Qwen2-VL-7B-Instruct-GPTQ-Int8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Local Apps Settings

How to use Qwen/Qwen2-VL-7B-Instruct-GPTQ-Int8 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Qwen/Qwen2-VL-7B-Instruct-GPTQ-Int8"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Qwen/Qwen2-VL-7B-Instruct-GPTQ-Int8",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/Qwen/Qwen2-VL-7B-Instruct-GPTQ-Int8

SGLang

How to use Qwen/Qwen2-VL-7B-Instruct-GPTQ-Int8 with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "Qwen/Qwen2-VL-7B-Instruct-GPTQ-Int8" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Qwen/Qwen2-VL-7B-Instruct-GPTQ-Int8",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "Qwen/Qwen2-VL-7B-Instruct-GPTQ-Int8" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Qwen/Qwen2-VL-7B-Instruct-GPTQ-Int8",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Docker Model Runner
How to use Qwen/Qwen2-VL-7B-Instruct-GPTQ-Int8 with Docker Model Runner:
```
docker model run hf.co/Qwen/Qwen2-VL-7B-Instruct-GPTQ-Int8
```

Qwen2-VL-7B-Instruct-GPTQ-Int8 / config.json

yangapku

feat(model) upload model

98f7e59 almost 2 years ago

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	{
	"_name_or_path": "Qwen/Qwen2-VL-7B-Instruct-319-PRO",
	"architectures": [
	"Qwen2VLForConditionalGeneration"
	],
	"attention_dropout": 0.0,
	"bos_token_id": 151643,
	"eos_token_id": 151645,
	"hidden_act": "silu",
	"hidden_size": 3584,
	"image_token_id": 151655,
	"initializer_range": 0.02,
	"intermediate_size": 18944,
	"max_position_embeddings": 32768,
	"max_window_layers": 28,
	"model_type": "qwen2_vl",
	"num_attention_heads": 28,
	"num_hidden_layers": 28,
	"num_key_value_heads": 4,
	"quantization_config": {
	"bits": 8,
	"damp_percent": 0.1,
	"dataset": null,
	"desc_act": false,
	"group_size": 128,
	"modules_in_block_to_quantize": null,
	"quant_method": "gptq",
	"sym": true,
	"true_sequential": true
	},
	"rms_norm_eps": 1e-06,
	"rope_scaling": {
	"mrope_section": [
	16,
	24,
	24
	],
	"type": "mrope"
	},
	"rope_theta": 1000000.0,
	"sliding_window": 32768,
	"tie_word_embeddings": false,
	"torch_dtype": "float16",
	"transformers_version": "4.45.0.dev0",
	"use_cache": true,
	"use_sliding_window": false,
	"video_token_id": 151656,
	"vision_config": {
	"in_chans": 3,
	"model_type": "qwen2_vl",
	"spatial_patch_size": 14
	},
	"vision_end_token_id": 151653,
	"vision_start_token_id": 151652,
	"vision_token_id": 151654,
	"vocab_size": 152064
	}