Image-Text-to-Text
Transformers
Safetensors
English
Chinese
qianfanvl_chat
feature-extraction
multimodal
ocr
document-understanding
conversational
custom_code
Instructions to use baidu/Qianfan-VL-70B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use baidu/Qianfan-VL-70B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="baidu/Qianfan-VL-70B", 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("baidu/Qianfan-VL-70B", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use baidu/Qianfan-VL-70B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "baidu/Qianfan-VL-70B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "baidu/Qianfan-VL-70B", "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/baidu/Qianfan-VL-70B
- SGLang
How to use baidu/Qianfan-VL-70B 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 "baidu/Qianfan-VL-70B" \ --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": "baidu/Qianfan-VL-70B", "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 "baidu/Qianfan-VL-70B" \ --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": "baidu/Qianfan-VL-70B", "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 baidu/Qianfan-VL-70B with Docker Model Runner:
docker model run hf.co/baidu/Qianfan-VL-70B
| # Copyright (c) 2025 Baidu | |
| # Licensed under the MIT License. See LICENSE file in the project root for full license information. | |
| import copy | |
| from transformers import AutoConfig, LlamaConfig | |
| from transformers.configuration_utils import PretrainedConfig | |
| from transformers.utils import logging | |
| from .configuration_intern_vit import InternVisionConfig | |
| logger = logging.get_logger(__name__) | |
| class QianfanVLChatConfig(PretrainedConfig): | |
| model_type = 'qianfanvl_chat' | |
| is_composition = True | |
| def __init__( | |
| self, | |
| vision_config=None, | |
| llm_config=None, | |
| use_backbone_lora=0, | |
| use_llm_lora=0, | |
| pad2square=False, | |
| select_layer=-1, | |
| force_image_size=None, | |
| downsample_ratio=0.5, | |
| template=None, | |
| dynamic_image_size=False, | |
| use_thumbnail=False, | |
| ps_version='v1', | |
| min_dynamic_patch=1, | |
| max_dynamic_patch=6, | |
| **kwargs): | |
| super().__init__(**kwargs) | |
| if vision_config is None: | |
| vision_config = {'architectures': ['InternVisionModel']} | |
| if llm_config is None: | |
| llm_config = {'architectures': ['LlamaForCausalLM']} | |
| self.vision_config = InternVisionConfig(**vision_config) | |
| self.llm_config = LlamaConfig(**llm_config) | |
| self.text_config = self.llm_config.get_text_config() | |
| self.use_backbone_lora = use_backbone_lora | |
| self.use_llm_lora = use_llm_lora | |
| self.pad2square = pad2square | |
| self.select_layer = select_layer | |
| self.force_image_size = force_image_size | |
| self.downsample_ratio = downsample_ratio | |
| self.template = template | |
| self.dynamic_image_size = dynamic_image_size | |
| self.use_thumbnail = use_thumbnail | |
| self.ps_version = ps_version # pixel shuffle version | |
| self.min_dynamic_patch = min_dynamic_patch | |
| self.max_dynamic_patch = max_dynamic_patch | |
| self.hidden_size = self.llm_config.hidden_size | |
| self.tie_word_embeddings = False | |
| self.llm_config.tie_word_embeddings = self.tie_word_embeddings | |
| def to_dict(self): | |
| """ | |
| Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`]. | |
| Returns: | |
| `Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance, | |
| """ | |
| output = copy.deepcopy(self.__dict__) | |
| output['vision_config'] = self.vision_config.to_dict() | |
| output['llm_config'] = self.llm_config.to_dict() | |
| output['text_config'] = self.text_config.to_dict() | |
| output['model_type'] = self.__class__.model_type | |
| output['use_backbone_lora'] = self.use_backbone_lora | |
| output['use_llm_lora'] = self.use_llm_lora | |
| output['select_layer'] = self.select_layer | |
| output['force_image_size'] = self.force_image_size | |
| output['downsample_ratio'] = self.downsample_ratio | |
| output['template'] = self.template | |
| output['dynamic_image_size'] = self.dynamic_image_size | |
| output['use_thumbnail'] = self.use_thumbnail | |
| output['ps_version'] = self.ps_version | |
| output['min_dynamic_patch'] = self.min_dynamic_patch | |
| output['max_dynamic_patch'] = self.max_dynamic_patch | |
| return output |