Instructions to use vikhyatk/moondream2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vikhyatk/moondream2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="vikhyatk/moondream2", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("vikhyatk/moondream2", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use vikhyatk/moondream2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "vikhyatk/moondream2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "vikhyatk/moondream2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/vikhyatk/moondream2
- SGLang
How to use vikhyatk/moondream2 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 "vikhyatk/moondream2" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "vikhyatk/moondream2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "vikhyatk/moondream2" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "vikhyatk/moondream2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use vikhyatk/moondream2 with Docker Model Runner:
docker model run hf.co/vikhyatk/moondream2
ImportError: cannot import name 'ToImage' from 'torchvision.transforms.v2' (D:\Miniconda\lib\site-packages\torchvision\transforms\v2\__init__.py)
calling torchvision.disable_beta_transforms_warning().
warnings.warn(BETA_TRANSFORMS_WARNING)
from torchvision.transforms.v2 import (
ImportError: cannot import name 'ToImage' from 'torchvision.transforms.v2' (D:\Miniconda\lib\site-packages\torchvision\transforms\v2_init.py)
What version of torchvision do you have installed? (You can check by running "pip show torchvision")
What version of torchvision do you have installed? (You can check by running "pip show torchvision")
Name: torchvision
Version: 0.16.2
Hey, I'm running into the same issue. As I understand it, ToImage was introduced in torchvision 0.16 (I'm running 0.15.2 due to my CUDA version). I think it could be replaced with the functional F.to_image. I'll try to find time to test it.
Edit:
Fixed using torchvision 0.15.2 by changing the preprocessor in vision_encoder.py
self.preprocess = Compose(
[
Resize(size=(378, 378), interpolation=InterpolationMode.BICUBIC, antialias=True),
ToTensor(),
ConvertImageDtype(torch.float32),
Normalize(mean=[0.5, 0.5, 0.5], std=[0.5, 0.5, 0.5]),
]