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, dtype="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
```

Error running code on Silicon M1 MAX

by tulas - opened Oct 10, 2024

Discussion

tulas

Oct 10, 2024

Any tips?

Loading checkpoint shards: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 7/7 [00:17<00:00, 2.49s/it]
Some parameters are on the meta device because they were offloaded to the disk.
Traceback (most recent call last):
File "/Users/tulas/Projects/molmo/main.py", line 31, in
output = model.generate_from_batch(
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/tulas/Projects/molmo/env/lib/python3.12/site-packages/torch/utils/_contextlib.py", line 116, in decorate_context
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/Users/tulas/.cache/huggingface/modules/transformers_modules/allenai/Molmo-7B-O-0924/1afe021df15873079d5c99ca1800d38acb23cd2d/modeling_molmo.py", line 2212, in generate_from_batch
out = super().generate(
^^^^^^^^^^^^^^^^^
File "/Users/tulas/Projects/molmo/env/lib/python3.12/site-packages/torch/utils/_contextlib.py", line 116, in decorate_context
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/Users/tulas/Projects/molmo/env/lib/python3.12/site-packages/transformers/generation/utils.py", line 2047, in generate
result = self._sample(
^^^^^^^^^^^^^
File "/Users/tulas/Projects/molmo/env/lib/python3.12/site-packages/transformers/generation/utils.py", line 3007, in _sample
outputs = self(**model_inputs, return_dict=True)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/tulas/Projects/molmo/env/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1553, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/tulas/Projects/molmo/env/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1562, in _call_impl
return forward_call(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/tulas/Projects/molmo/env/lib/python3.12/site-packages/accelerate/hooks.py", line 170, in new_forward
output = module._old_forward(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/tulas/.cache/huggingface/modules/transformers_modules/allenai/Molmo-7B-O-0924/1afe021df15873079d5c99ca1800d38acb23cd2d/modeling_molmo.py", line 2106, in forward
outputs = self.model.forward(
^^^^^^^^^^^^^^^^^^^
File "/Users/tulas/.cache/huggingface/modules/transformers_modules/allenai/Molmo-7B-O-0924/1afe021df15873079d5c99ca1800d38acb23cd2d/modeling_molmo.py", line 1920, in forward
attention_bias = get_causal_attention_bias(self.__cache, past_length + seq_len, x.device)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/tulas/.cache/huggingface/modules/transformers_modules/allenai/Molmo-7B-O-0924/1afe021df15873079d5c99ca1800d38acb23cd2d/modeling_molmo.py", line 1565, in get_causal_attention_bias
with torch.autocast(device.type, enabled=False):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/tulas/Projects/molmo/env/lib/python3.12/site-packages/torch/amp/autocast_mode.py", line 229, in init
dtype = torch.get_autocast_dtype(device_type)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
RuntimeError: unsupported scalarType

amanrangapur

Oct 28, 2024

•

edited Nov 8, 2024

Hello @Troubadix I tried to replicate this and resolve, but it seems to be an issue with Torch, as other models throw the same error. This thread discusses bfloat16 support for operations. However, from my investigation, autocast only works with CPU and CUDA device types. I’ll look into this further and update you if I find anything. A few useful threads.. [1 2].

tulas

Oct 28, 2024

thank you @amanrangapur !

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