Instructions to use prem-research/Premonition-Exp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use prem-research/Premonition-Exp with Transformers:

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

pipe = pipeline("image-text-to-text", model="prem-research/Premonition-Exp", 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 AutoModelForImageTextToText
model = AutoModelForImageTextToText.from_pretrained("prem-research/Premonition-Exp", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use prem-research/Premonition-Exp with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "prem-research/Premonition-Exp"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "prem-research/Premonition-Exp",
		"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/prem-research/Premonition-Exp

SGLang

How to use prem-research/Premonition-Exp 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 "prem-research/Premonition-Exp" \
    --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": "prem-research/Premonition-Exp",
		"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 "prem-research/Premonition-Exp" \
        --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": "prem-research/Premonition-Exp",
		"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 prem-research/Premonition-Exp with Docker Model Runner:
```
docker model run hf.co/prem-research/Premonition-Exp
```

Premonition-Exp / NOTICE

ojus1

Add trained Gemma 4 audio graft projector, full checkpoint, usage and multimodal demo

b965204 verified about 1 month ago

Raw History Blame Contribute Delete

556 Bytes

Premonition-Exp architecture graft and assembly tooling
Copyright 2026 Prem Research.

Contains unchanged DiffusionGemma backbone and Gemma 4 E4B audio tower weights.
A lightweight audio projector was trained for the Gemma 4 audio graft.
Source model identifiers and immutable revisions appear in assembly_manifest.json.

Hugging Face Transformers: Copyright The Hugging Face team.
Gemma 4 / DiffusionGemma model weights: Google / Google DeepMind.
vLLM: Copyright contributors to the vLLM project.
Not affiliated with or endorsed by Google or TypeSafe AI.

	Premonition-Exp architecture graft and assembly tooling
	Copyright 2026 Prem Research.

	Contains unchanged DiffusionGemma backbone and Gemma 4 E4B audio tower weights.
	A lightweight audio projector was trained for the Gemma 4 audio graft.
	Source model identifiers and immutable revisions appear in assembly_manifest.json.

	Hugging Face Transformers: Copyright The Hugging Face team.
	Gemma 4 / DiffusionGemma model weights: Google / Google DeepMind.
	vLLM: Copyright contributors to the vLLM project.
	Not affiliated with or endorsed by Google or TypeSafe AI.