Instructions to use 5CD-AI/Vintern-1B-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 5CD-AI/Vintern-1B-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="5CD-AI/Vintern-1B-v2", 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("5CD-AI/Vintern-1B-v2", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use 5CD-AI/Vintern-1B-v2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "5CD-AI/Vintern-1B-v2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "5CD-AI/Vintern-1B-v2", "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/5CD-AI/Vintern-1B-v2
- SGLang
How to use 5CD-AI/Vintern-1B-v2 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 "5CD-AI/Vintern-1B-v2" \ --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": "5CD-AI/Vintern-1B-v2", "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 "5CD-AI/Vintern-1B-v2" \ --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": "5CD-AI/Vintern-1B-v2", "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 5CD-AI/Vintern-1B-v2 with Docker Model Runner:
docker model run hf.co/5CD-AI/Vintern-1B-v2
TypeErorr: got multiple values for keyword argument 'return_dict'
I encountered this error when trying to run the model test:
TypeError: Qwen2ForCausalLM(
(model): Qwen2Model(
(embed_tokens): Embedding(151655, 896)
(layers): ModuleList(
(0-23): 24 x Qwen2DecoderLayer(
(self_attn): Qwen2Attention(
(q_proj): Linear(in_features=896, out_features=896, bias=True)
(k_proj): Linear(in_features=896, out_features=128, bias=True)
(v_proj): Linear(in_features=896, out_features=128, bias=True)
(o_proj): Linear(in_features=896, out_features=896, bias=False)
(rotary_emb): Qwen2RotaryEmbedding()
)
(mlp): Qwen2MLP(
(gate_proj): Linear(in_features=896, out_features=4864, bias=False)
(up_proj): Linear(in_features=896, out_features=4864, bias=False)
(down_proj): Linear(in_features=4864, out_features=896, bias=False)
(act_fn): SiLU()
)
(input_layernorm): Qwen2RMSNorm((896,), eps=1e-06)
(post_attention_layernorm): Qwen2RMSNorm((896,), eps=1e-06)
)
)
(norm): Qwen2RMSNorm((896,), eps=1e-06)
(rotary_emb): Qwen2RotaryEmbedding()
)
(lm_head): Linear(in_features=896, out_features=151655, bias=False)
) got multiple values for keyword argument 'return_dict'
please upgrade your transformers lib
I upgraded the Transformers library, but the error still occurs. How to fix it?
oh. please install pip install transformers==4.37.2, it will work fine :)
It worked, thanks for your help