Image-Text-to-Text
Transformers
TensorBoard
Safetensors
multilingual
internvl_chat
feature-extraction
internvl
custom_code
conversational
Instructions to use OpenGVLab/InternVL-Chat-V1-5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenGVLab/InternVL-Chat-V1-5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="OpenGVLab/InternVL-Chat-V1-5", 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("OpenGVLab/InternVL-Chat-V1-5", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use OpenGVLab/InternVL-Chat-V1-5 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "OpenGVLab/InternVL-Chat-V1-5" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OpenGVLab/InternVL-Chat-V1-5", "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/OpenGVLab/InternVL-Chat-V1-5
- SGLang
How to use OpenGVLab/InternVL-Chat-V1-5 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 "OpenGVLab/InternVL-Chat-V1-5" \ --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": "OpenGVLab/InternVL-Chat-V1-5", "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 "OpenGVLab/InternVL-Chat-V1-5" \ --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": "OpenGVLab/InternVL-Chat-V1-5", "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 OpenGVLab/InternVL-Chat-V1-5 with Docker Model Runner:
docker model run hf.co/OpenGVLab/InternVL-Chat-V1-5
BugFix: AttributeError: 'InternVLChatConfig' object has no attribute 'llm_config'
#29
by snowleopard-mllm - opened
When loading InternVideo2_5_Chat_8B model or InternVL2_5 series models:
It raises AttributeError: 'InternVLChatConfig' object has no attribute 'llm_config'
Please refer: https://huggingface.co/OpenGVLab/InternVideo2_5_Chat_8B/discussions/14
Simple Solution for InternVL Configuration Issue
(Tested with transformers v4.52.4)
Required Modifications
Add Initialization (configuration_internvl_chat.py:49)
self.vision_config = InternVisionConfig(**vision_config) self.llm_config = None # Initialize llm_config to prevent AttributeErrorAdd Null Check (configuration_internvl_chat.py:85)
output['llm_config'] = self.llm_config.to_dict() if self.llm_config is not None else {}
Root Cause Analysis
When executing:
model = AutoModel.from_pretrained(model_path, trust_remote_code=True).half().cuda().to(torch.bfloat16)
The following occurs:
- The Hugging Face framework downloads and parses
configuration_internvl_chat.py - During config initialization (
transformers/configuration_utils.py:816-822):config_dict = self.to_dict() # Get the default config dict (from a fresh PreTrainedConfig instance) default_config_dict = PretrainedConfig().to_dict() # get class specific config dict class_config_dict = self.__class__().to_dict() if not self.has_no_defaults_at_init else {} - Key Issue:
self.llm_configisNoneduringclass_config_dictgeneration becausellm_configis None- Without explicit initialization, this triggers an
AttributeErrorwhen.to_dict()is called
Why the Fix Works
- The initialization ensures
self.llm_configalways exists (even asNone) - The null check prevents method calls on
Nonewhile maintaining expected dictionary structure