Image-Text-to-Text
Transformers
Safetensors
English
molmo
text-generation
multimodal
olmo
pixmo
conversational
custom_code
Instructions to use allenai/Molmo-7B-D-0924 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use allenai/Molmo-7B-D-0924 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="allenai/Molmo-7B-D-0924", 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)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("allenai/Molmo-7B-D-0924", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use allenai/Molmo-7B-D-0924 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "allenai/Molmo-7B-D-0924" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "allenai/Molmo-7B-D-0924", "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/allenai/Molmo-7B-D-0924
- SGLang
How to use allenai/Molmo-7B-D-0924 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 "allenai/Molmo-7B-D-0924" \ --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": "allenai/Molmo-7B-D-0924", "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 "allenai/Molmo-7B-D-0924" \ --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": "allenai/Molmo-7B-D-0924", "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 allenai/Molmo-7B-D-0924 with Docker Model Runner:
docker model run hf.co/allenai/Molmo-7B-D-0924
Update modeling_molmo to work with transformers 4.56.2
Browse filesAvoid errors like this:
```
[rank0]: past_length = past_key_values[0][0].size(-2)
[rank0]: AttributeError: 'NoneType' object has no attribute 'size'
```
- modeling_molmo.py +5 -0
modeling_molmo.py
CHANGED
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@@ -2226,6 +2226,11 @@ class MolmoForCausalLM(PreTrainedModel):
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def prepare_inputs_for_generation(
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self, input_ids: torch.LongTensor, past_key_values: Optional[List[Tuple]] = None, **kwargs
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):
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if past_key_values:
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# This is because we want the model to only process the last generated token.
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input_ids = input_ids[:, -1:]
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def prepare_inputs_for_generation(
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self, input_ids: torch.LongTensor, past_key_values: Optional[List[Tuple]] = None, **kwargs
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):
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+
has_past_key_values = past_key_values is not None and any (x != (None, None) for x in past_key_values)
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if not has_past_key_values:
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# Override a list of (None, None) tuples with a single None value as expected by the rest of the code
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past_key_values = None
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if past_key_values:
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# This is because we want the model to only process the last generated token.
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input_ids = input_ids[:, -1:]
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