Instructions to use allenai/MolmoWeb-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use allenai/MolmoWeb-4B with Transformers:

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

pipe = pipeline("image-text-to-text", model="allenai/MolmoWeb-4B", 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/MolmoWeb-4B", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use allenai/MolmoWeb-4B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "allenai/MolmoWeb-4B"
# 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/MolmoWeb-4B",
		"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/MolmoWeb-4B

SGLang

How to use allenai/MolmoWeb-4B 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/MolmoWeb-4B" \
    --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/MolmoWeb-4B",
		"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/MolmoWeb-4B" \
        --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/MolmoWeb-4B",
		"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/MolmoWeb-4B with Docker Model Runner:
```
docker model run hf.co/allenai/MolmoWeb-4B
```

Updated template and image processing code to match native exactly

by zixianma02 - opened Mar 30

base: refs/heads/main

←

from: refs/pr/1

Discussion Files changed

-3

Files changed (2) hide show

chat_template.jinja +1 -1
image_processing_molmo2.py +2 -2

chat_template.jinja CHANGED Viewed

@@ -1 +1 @@

- {% set DEMO_STYLES = ['point_count','pointing','cosyn_point','user_qa','long_caption','short_caption','video_long_caption','video_short_caption','video_point_track_per_frame','video_point_track_start_end','video_point_track_all_frames','video_single_point_track_start_end','video_transcript','video_clip_caption_start_end','video_clip_caption_start_end_in_seconds','video_clip_transcript_start_end','video_clip_transcript_start_end_in_seconds','video_frame_caption_timestamp','video_frame_caption_timestamp_in_seconds','correction_qa','text_sft','video_point','video_point_count','video_count','video_count_point','multi_image_pointing','multi_image_counting','multi_image_point_then_count','multi_image_count_then_point','demo','a_okvqa_mc','ai2_diagram_no_letter','ai2_diagram','science_qa','multi_image_mc','multi_image_mc_exp','mantis_instruct_mc','video_multiple_choice','video_multiple_choice_count_without_pointing','video_multiple_choice_multiple_correct','video_multiple_choice_w_subtitle'] %}{% set image_count = namespace(value=0) %}{% set video_count = namespace(value=0) %}{% set has_subtitle = messages and messages[0]['role'].lower() == 'subtitle' %}{% for message in messages %}{% if message['content'] is not string %}{% for content in message['content'] %}{% if content['type'] == 'image' or 'image' in content or 'image_url' in content %}{% set image_count.value = image_count.value + 1 %}{% elif content['type'] == 'video' or 'video' in content or 'video_url' in content %}{% set video_count.value = video_count.value + 1 %}{% endif %}{% endfor %}{% endif %}{% endfor %}{% if image_count.value == 1 %}{{ '<|image|>' }}{% elif image_count.value > 1 %}{% for i in range(image_count.value) %}{{ 'Image ' ~ (i + 1) ~ '<|image|>' }}{% endfor %}{% endif %}{% for _ in range(video_count.value) %}{{ '<|video|>' }}{% endfor %}{% if has_subtitle %}{{ messages[0]['content'] }}{% endif %}{% for message in messages %}{% set role = message['role'].lower() %}{% if role == 'subtitle' %}{% continue %}{% endif %}{% set conv_index = loop.index - (1 if has_subtitle else 0) %}{%- if (conv_index % 2 == 1 and role != 'user') or (conv_index % 2 == 0 and role != 'assistant') -%}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{%- endif -%}{% if message['content'] is string %}{% set text_content = message['content'] %}{% else %}{% set m = namespace(text='') %}{% for content in message['content'] %}{% if content['type'] == 'text' %}{% if content['style'] is defined and content['style'] not in DEMO_STYLES %}{% set seg = content['style'] ~ ': ' ~ content['text'] %}{% else %}{% set seg = content['text'] %}{% endif %}{% set m.text = m.text ~ ('' if not m.text else ' ') ~ seg %}{% endif %}{% endfor %}{% set text_content = m.text %}{% endif %}{% if role == 'user' %}{% ~~if not (has_subtitle and loop.index == 2) and not (not has_subtitle and loop.first) %}~~{{ ~~'<|im_end|>\n' }}{% endif %}{{ '<|im_start|>user\n' }}{{~~ text_content }}{~~{ '<|im_end|>\n' }}{~~% else %} {~~# assistant #}~~{{ ~~'<|im_start|>assistant\n' }}{{~~ text_content }}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ ~~'<|im_start|>assistant\n' }}~~{% endif %}

+ {% set DEMO_STYLES = ['point_count','pointing','cosyn_point','user_qa','long_caption','short_caption','video_long_caption','video_short_caption','video_point_track_per_frame','video_point_track_start_end','video_point_track_all_frames','video_single_point_track_start_end','video_transcript','video_clip_caption_start_end','video_clip_caption_start_end_in_seconds','video_clip_transcript_start_end','video_clip_transcript_start_end_in_seconds','video_frame_caption_timestamp','video_frame_caption_timestamp_in_seconds','correction_qa','text_sft','video_point','video_point_count','video_count','video_count_point','multi_image_pointing','multi_image_counting','multi_image_point_then_count','multi_image_count_then_point','demo','a_okvqa_mc','ai2_diagram_no_letter','ai2_diagram','science_qa','multi_image_mc','multi_image_mc_exp','mantis_instruct_mc','video_multiple_choice','video_multiple_choice_count_without_pointing','video_multiple_choice_multiple_correct','video_multiple_choice_w_subtitle'] %}{% set image_count = namespace(value=0) %}{% set video_count = namespace(value=0) %}{% set has_subtitle = messages and messages[0]['role'].lower() == 'subtitle' %}{% for message in messages %}{% if message['content'] is not string %}{% for content in message['content'] %}{% if content['type'] == 'image' or 'image' in content or 'image_url' in content %}{% set image_count.value = image_count.value + 1 %}{% elif content['type'] == 'video' or 'video' in content or 'video_url' in content %}{% set video_count.value = video_count.value + 1 %}{% endif %}{% endfor %}{% endif %}{% endfor %}{% if image_count.value == 1 %}{{ '<|image|>' }}{% elif image_count.value > 1 %}{% for i in range(image_count.value) %}{{ 'Image ' ~ (i + 1) ~ '<|image|>' }}{% endfor %}{% endif %}{% for _ in range(video_count.value) %}{{ '<|video|>' }}{% endfor %}{% if has_subtitle %}{{ messages[0]['content'] }}{% endif %}{% for message in messages %}{% set role = message['role'].lower() %}{% if role == 'subtitle' %}{% continue %}{% endif %}{% set conv_index = loop.index - (1 if has_subtitle else 0) %}{%- if (conv_index % 2 == 1 and role != 'user') or (conv_index % 2 == 0 and role != 'assistant') -%}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{%- endif -%}{% if message['content'] is string %}{% set text_content = message['content'] %}{% else %}{% set m = namespace(text='') %}{% for content in message['content'] %}{% if content['type'] == 'text' %}{% if content['style'] is defined and content['style'] not in DEMO_STYLES %}{% set seg = content['style'] ~ ': ' ~ content['text'] %}{% else %}{% set seg = content['text'] %}{% endif %}{% set m.text = m.text ~ ('' if not m.text else ' ') ~ seg %}{% endif %}{% endfor %}{% set text_content = m.text %}{% endif %}{% if role == 'user' %}User: {{ text_content }}{% else %} {{ text_content }}{% endif %}{% endfor %}{% if add_generation_prompt %} Assistant:{% endif %}

image_processing_molmo2.py CHANGED Viewed

@@ -156,8 +156,8 @@ def build_overlapping_crops(
     # Decide how to tile the image, to account for the overlap margins we compute the tiling
     # as if we had an image without the margins and were using a crop size without the margins
     tiling = select_tiling(
-        original_image_h - total_margin_pixels,
-        original_image_w - total_margin_pixels,
         crop_window_size,
         max_crops,
     )

     # Decide how to tile the image, to account for the overlap margins we compute the tiling
     # as if we had an image without the margins and were using a crop size without the margins
     tiling = select_tiling(
+        max(original_image_h - total_margin_pixels, 1),
+        max(original_image_w - total_margin_pixels, 1),
         crop_window_size,
         max_crops,
     )