Instructions to use allenai/Molmo-7B-O-0924 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use allenai/Molmo-7B-O-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-O-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)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("allenai/Molmo-7B-O-0924", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use allenai/Molmo-7B-O-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-O-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-O-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-O-0924

SGLang

How to use allenai/Molmo-7B-O-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-O-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-O-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-O-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-O-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-O-0924 with Docker Model Runner:
```
docker model run hf.co/allenai/Molmo-7B-O-0924
```

syhuggingface commited on Jun 18, 2025

Commit

1f923ce

verified ·

1 Parent(s): 0e72795

Update modeling_molmo.py for compatibility

Browse files

Make code compatible with transformers >= 4.50.3.
Update code to align with recent changes in the Transformers library (calling _extract_past_from_model_output() raises an error).

Same PR from `allenai/Molmo-7B-D-0924`
https://huggingface.co/allenai/Molmo-7B-D-0924/discussions/43

Files changed (1) hide show

modeling_molmo.py +5 -0

modeling_molmo.py CHANGED Viewed

@@ -2273,6 +2273,11 @@ class MolmoForCausalLM(PreTrainedModel):
                 del model_kwargs["image_masks"]
                 del model_kwargs["image_input_idx"]
         cache_name, cache = super()._extract_past_from_model_output(outputs)
         model_kwargs[cache_name] = cache
         model_kwargs["cache_position"] = model_kwargs["cache_position"][-1:] + num_new_tokens
         return model_kwargs

                 del model_kwargs["image_masks"]
                 del model_kwargs["image_input_idx"]
         cache_name, cache = super()._extract_past_from_model_output(outputs)
+        try:
+            cache_name, cache = super()._extract_past_from_model_output(outputs)
+        except AttributeError:
+            past_key_values = outputs.past_key_values if "past_key_values" in outputs else None
+            cache_name, cache = "past_key_values", past_key_values
         model_kwargs[cache_name] = cache
         model_kwargs["cache_position"] = model_kwargs["cache_position"][-1:] + num_new_tokens
         return model_kwargs