Image-Text-to-Text
Transformers
Safetensors
English
qwen2_5_vl
multimodal
conversational
text-generation-inference
4-bit precision
awq
Instructions to use Qwen/Qwen2.5-VL-32B-Instruct-AWQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Qwen/Qwen2.5-VL-32B-Instruct-AWQ with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="Qwen/Qwen2.5-VL-32B-Instruct-AWQ") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("Qwen/Qwen2.5-VL-32B-Instruct-AWQ") model = AutoModelForMultimodalLM.from_pretrained("Qwen/Qwen2.5-VL-32B-Instruct-AWQ", device_map="auto") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] inputs = processor.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Qwen/Qwen2.5-VL-32B-Instruct-AWQ with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Qwen/Qwen2.5-VL-32B-Instruct-AWQ" # 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/Qwen2.5-VL-32B-Instruct-AWQ", "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/Qwen2.5-VL-32B-Instruct-AWQ
- SGLang
How to use Qwen/Qwen2.5-VL-32B-Instruct-AWQ 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/Qwen2.5-VL-32B-Instruct-AWQ" \ --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/Qwen2.5-VL-32B-Instruct-AWQ", "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/Qwen2.5-VL-32B-Instruct-AWQ" \ --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/Qwen2.5-VL-32B-Instruct-AWQ", "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/Qwen2.5-VL-32B-Instruct-AWQ with Docker Model Runner:
docker model run hf.co/Qwen/Qwen2.5-VL-32B-Instruct-AWQ
some weights not initialized problem with transformers library.
ππ 9
4
#13 opened over 1 year ago
by
robotrule
Update README.md
#12 opened over 1 year ago
by
hemantho
(vLLM) Tool calling broken after update to tokenizer_config.json
1
#10 opened over 1 year ago
by
m1das13
RuntimeError: expected mat1 and mat2 to have the same dtype, but got: struct c10::Half != struct c10::BFloat16
5
#9 opened over 1 year ago
by
rameshch
AssertionError: Both operands must be same dtype. Got fp16 and bf16
20
#8 opened over 1 year ago
by
treehugg3
can it work on single 3090?
2
#7 opened over 1 year ago
by
hamaadtahiir
Model does not produce meaningful output for VQA
π 1
1
#6 opened over 1 year ago
by
rpeinl
The inference speed of the AWQ model is slower than that of the original model
#4 opened over 1 year ago
by
wakakakakawa
Quality issues with AWQ Model
4
#3 opened over 1 year ago
by
bggmyfuture-ai
Should have a `image_processor_type` key
π 3
1
#2 opened over 1 year ago
by
Gierry
Unrecognized image processor in Qwen/Qwen2.5-VL-32B-Instruct-AWQ.
βπ 2
2
#1 opened over 1 year ago
by
acidz1