Image-Text-to-Text
Transformers
Safetensors
English
qwen2_5vl_ca
feature-extraction
conversational
custom_code
Instructions to use kyutai/CASA-Qwen2_5-VL-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kyutai/CASA-Qwen2_5-VL-3B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="kyutai/CASA-Qwen2_5-VL-3B", trust_remote_code=True) 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 AutoModel model = AutoModel.from_pretrained("kyutai/CASA-Qwen2_5-VL-3B", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use kyutai/CASA-Qwen2_5-VL-3B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "kyutai/CASA-Qwen2_5-VL-3B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "kyutai/CASA-Qwen2_5-VL-3B", "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/kyutai/CASA-Qwen2_5-VL-3B
- SGLang
How to use kyutai/CASA-Qwen2_5-VL-3B 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 "kyutai/CASA-Qwen2_5-VL-3B" \ --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": "kyutai/CASA-Qwen2_5-VL-3B", "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 "kyutai/CASA-Qwen2_5-VL-3B" \ --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": "kyutai/CASA-Qwen2_5-VL-3B", "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 kyutai/CASA-Qwen2_5-VL-3B with Docker Model Runner:
docker model run hf.co/kyutai/CASA-Qwen2_5-VL-3B
Download configuration_qwen2_5vl_ca.py from kyutai/CASA-Qwen2_5-VL-3B: direct link, hf CLI and curl.
- Browser
- Download file 1.17 kB
-
https://huggingface.co/kyutai/CASA-Qwen2_5-VL-3B/resolve/5f7de59b9176f39e65882ab7f22fbebdcd5dc0a6/configuration_qwen2_5vl_ca.py
- Command line
-
hf download hf://kyutai/CASA-Qwen2_5-VL-3B@5f7de59b9176f39e65882ab7f22fbebdcd5dc0a6/configuration_qwen2_5vl_ca.py
-
curl -L -o configuration_qwen2_5vl_ca.py https://huggingface.co/kyutai/CASA-Qwen2_5-VL-3B/resolve/5f7de59b9176f39e65882ab7f22fbebdcd5dc0a6/configuration_qwen2_5vl_ca.py
1.17 kB
| from typing import Any | |
| from transformers.models.qwen2_5_vl.configuration_qwen2_5_vl import Qwen2_5_VLConfig | |
| class Qwen2_5_VLCAConfig(Qwen2_5_VLConfig): | |
| """Qwen2.5-VL config augmented with cross-attention options""" | |
| model_type = "qwen2_5vl_ca" | |
| def __init__( | |
| self, | |
| *args: Any, | |
| # Our fusion mechanism | |
| xa_layers: None | tuple = None, | |
| cross_attention: bool = False, | |
| xa_share_qkvo: bool = False, | |
| **kwargs: Any, | |
| ): | |
| super().__init__(*args, **kwargs) | |
| self.head_dim = self.hidden_size // self.num_attention_heads | |
| # Our fusion mechanisms | |
| self.xa_layers = xa_layers | |
| self.cross_attention = cross_attention | |
| self.xa_share_qkvo = xa_share_qkvo | |
| # Derived from vision_start/end_token_id set by parent | |
| self.pre_image_tokens = ( | |
| [self.vision_start_token_id] | |
| if getattr(self, "vision_start_token_id", None) is not None | |
| else [] | |
| ) | |
| self.post_image_tokens = ( | |
| [self.vision_end_token_id] | |
| if getattr(self, "vision_end_token_id", None) is not None | |
| else [] | |
| ) | |