Instructions to use openbmb/MiniCPM-Llama3-V-2_5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use openbmb/MiniCPM-Llama3-V-2_5 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("image-text-to-text", model="openbmb/MiniCPM-Llama3-V-2_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("openbmb/MiniCPM-Llama3-V-2_5", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use openbmb/MiniCPM-Llama3-V-2_5 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "openbmb/MiniCPM-Llama3-V-2_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": "openbmb/MiniCPM-Llama3-V-2_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/openbmb/MiniCPM-Llama3-V-2_5

SGLang

How to use openbmb/MiniCPM-Llama3-V-2_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 "openbmb/MiniCPM-Llama3-V-2_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": "openbmb/MiniCPM-Llama3-V-2_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 "openbmb/MiniCPM-Llama3-V-2_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": "openbmb/MiniCPM-Llama3-V-2_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 openbmb/MiniCPM-Llama3-V-2_5 with Docker Model Runner:
```
docker model run hf.co/openbmb/MiniCPM-Llama3-V-2_5
```

Why doesn't it work with bitsnbytes 8 or 4bit?

#25

by jackboot - opened Jun 4, 2024

Discussion

jackboot

Jun 4, 2024

I have tried to load the model using bitsnbytes but unfortunately there is a type error on inference.

File "/home/supermicro/ai/openedai-vision/backend/minicpm.py", line 54, in chat_with_images answer = self.model.chat( File "/home/supermicro/.cache/huggingface/modules/transformers_modules/MiniCPM-Llama3-V-2_5/modeling_minicpmv.py", line 454, in chat res, vision_hidden_states = self.generate( File "/home/supermicro/.cache/huggingface/modules/transformers_modules/MiniCPM-Llama3-V-2_5/modeling_minicpmv.py", line 354, in generate ) = self.get_vllm_embedding(model_inputs) File "/home/supermicro/.cache/huggingface/modules/transformers_modules/MiniCPM-Llama3-V-2_5/modeling_minicpmv.py", line 100, in get_vllm_embedding vision_embedding = self.resampler(vision_embedding, tgt_sizes) File "/home/supermicro/miniconda3/envs/nvidia/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl return self._call_impl(*args, **kwargs) File "/home/supermicro/miniconda3/envs/nvidia/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl return forward_call(*args, **kwargs) File "/home/supermicro/miniconda3/envs/nvidia/lib/python3.10/site-packages/accelerate/hooks.py", line 166, in new_forward output = module._old_forward(*args, **kwargs) File "/home/supermicro/.cache/huggingface/modules/transformers_modules/MiniCPM-Llama3-V-2_5/resampler.py", line 150, in forward out = self.attn( File "/home/supermicro/miniconda3/envs/nvidia/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl return self._call_impl(*args, **kwargs) File "/home/supermicro/miniconda3/envs/nvidia/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl return forward_call(*args, **kwargs) File "/home/supermicro/miniconda3/envs/nvidia/lib/python3.10/site-packages/accelerate/hooks.py", line 166, in new_forward output = module._old_forward(*args, **kwargs) File "/home/supermicro/miniconda3/envs/nvidia/lib/python3.10/site-packages/torch/nn/modules/activation.py", line 1266, in forward attn_output, attn_output_weights = F.multi_head_attention_forward( File "/home/supermicro/miniconda3/envs/nvidia/lib/python3.10/site-packages/torch/nn/functional.py", line 5477, in multi_head_attention_forward attn_output = linear(attn_output, out_proj_weight, out_proj_bias) RuntimeError: self and mat2 must have the same dtype, but got BFloat16 and Char

Did anyone figure out why this could be? It loads fine in transformers and inferences. Not sure how the dtype ends up char.

jackboot

Jun 4, 2024

heh, after I posted this I tried

llm_int8_skip_modules= ["resampler"]

Seems to be inferencing. So the resampler can't be quantized?

vramesh

Jun 6, 2024

@jackboot Would you mind sharing your bitsnbytes config? Have a single T4 Nvidia and the only config it works on is when loading in 4-bits.

jackboot

Jun 7, 2024

            'quantization_config': BitsAndBytesConfig(
                load_in_4bit=True,
                bnb_4bit_quant_type='nf4',
                bnb_4bit_use_double_quant=True, 
                bnb_4bit_compute_dtype=self.dtype,
                llm_int8_skip_modules= ["resampler"]

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