Instructions to use moondream/moondream3-preview with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use moondream/moondream3-preview with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="moondream/moondream3-preview", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("moondream/moondream3-preview", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use moondream/moondream3-preview with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "moondream/moondream3-preview" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "moondream/moondream3-preview", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/moondream/moondream3-preview
- SGLang
How to use moondream/moondream3-preview 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 "moondream/moondream3-preview" \ --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": "moondream/moondream3-preview", "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 "moondream/moondream3-preview" \ --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": "moondream/moondream3-preview", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use moondream/moondream3-preview with Docker Model Runner:
docker model run hf.co/moondream/moondream3-preview
AttributeError: 'HfMoondream' object has no attribute 'all_tied_weights_keys'. Did you mean: '_tied_weights_keys'?
AttributeError: 'HfMoondream' object has no attribute 'all_tied_weights_keys'. Did you mean: '_tied_weights_keys'?
anyone can help fix this?
because I want use this model but I have this error
same for stable(5.0.0) and latest from git
I bet you have too new transformers...
try reverting to a bit older transformers (4.x), this fixed the issue for me.
pip install "transformers<5.0.0"
I guess the actual error is in the initialization of the model and it's device_map attribute, anyhow this is a guess. YOu could maybe move the model to cuda manually later?
not working
same problem
not working
same problem
Try calling model.post_init() right after model construction. That might fix your issue. Most likely due to the transformers version like Kelmeilia mentioned
any update on this?
Use below code
import torch
_orig_getattr = torch.nn.Module.__getattr__
def _patched_getattr(self, name):
if name == "all_tied_weights_keys":
return {}
return _orig_getattr(self, name)
torch.nn.Module.__getattr__ = _patched_getattr
@Clausss @jaabir as @Kelmeilia suggested, you have too new of a HF version (v5.0.0 changed some names). If you use an older transformers version, such as 4.56.1, it will work.
pip install transformers==4.56.1