Instructions to use allenai/Molmo2-ER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use allenai/Molmo2-ER with Transformers:

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

pipe = pipeline("image-text-to-text", model="allenai/Molmo2-ER", 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 AutoModelForImageTextToText
model = AutoModelForImageTextToText.from_pretrained("allenai/Molmo2-ER", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use allenai/Molmo2-ER with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "allenai/Molmo2-ER"
# 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/Molmo2-ER",
		"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/Molmo2-ER

SGLang

How to use allenai/Molmo2-ER 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/Molmo2-ER" \
    --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/Molmo2-ER",
		"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/Molmo2-ER" \
        --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/Molmo2-ER",
		"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/Molmo2-ER with Docker Model Runner:
```
docker model run hf.co/allenai/Molmo2-ER
```

weikaih commited on 3 days ago

Commit

1e5a25f

verified ·

1 Parent(s): 613949f

README: drop inline inference example, point to molmo2 repo

Browse files

Files changed (1) hide show

README.md +2 -45

README.md CHANGED Viewed

@@ -42,52 +42,9 @@ All other hyperparameters follow [Molmo2](https://github.com/allenai/molmo2).
 - **Code**: https://github.com/allenai/molmo2
 - **Base model**: [Molmo2-4B](https://github.com/allenai/molmo2)
-## Inference
-```python
-from transformers import AutoProcessor, AutoModelForImageTextToText
-from PIL import Image
-import requests
-import torch
-model = AutoModelForImageTextToText.from_pretrained(
-    "allenai/Molmo2-ER-4B",
-    trust_remote_code=True,
-    dtype="auto",
-    device_map="auto",
-)
-processor = AutoProcessor.from_pretrained(
-    "allenai/Molmo2-ER-4B",
-    trust_remote_code=True,
-    padding_side="left",
-)
-messages = [{
-    "role": "user",
-    "content": [
-        {"type": "text", "text": "Point to the apple."},
-        {"type": "image", "image": Image.open(requests.get(
-            "https://picsum.photos/id/237/536/354", stream=True
-        ).raw)},
-    ],
-}]
-inputs = processor.apply_chat_template(
-    messages,
-    tokenize=True,
-    add_generation_prompt=True,
-    return_tensors="pt",
-    return_dict=True,
-    padding=True,
-)
-inputs = {k: v.to("cuda") for k, v in inputs.items()}
-with torch.inference_mode(), torch.autocast("cuda", dtype=torch.bfloat16):
-    output = model.generate(**inputs, max_new_tokens=256)
-print(processor.decode(output[0, inputs["input_ids"].size(1):], skip_special_tokens=True))
-```
 ## License

 - **Code**: https://github.com/allenai/molmo2
 - **Base model**: [Molmo2-4B](https://github.com/allenai/molmo2)
+## Usage
+See https://github.com/allenai/molmo2 for inference, evaluation, and training code.
 ## License