Image-Text-to-Text
Transformers
Safetensors
premonition_diffusion_gemma
vllm
diffusion-gemma
multimodal
audio
video
custom_code
conversational
Instructions to use prem-research/Premonition-Exp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
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
Make enterprise walkthrough silent
Browse files- README.md +1 -1
- demo/premonition-enterprise.mp4 +2 -2
README.md
CHANGED
|
@@ -25,7 +25,7 @@ The checkpoint accepts **text, images, video and audio**, including mixed inputs
|
|
| 25 |
|
| 26 |
[Open the video](https://huggingface.co/prem-research/Premonition-Exp/resolve/main/demo/premonition-enterprise.mp4).
|
| 27 |
|
| 28 |
-
The walkthrough records actual API calls using fictional business scenarios: a purchase policy, invoice routing, a schematic warehouse handoff, customer voicemail and a combined evidence packet. The accompanying fixtures and replay script are included in this repository.
|
| 29 |
|
| 30 |
## Install the serving environment
|
| 31 |
|
|
|
|
| 25 |
|
| 26 |
[Open the video](https://huggingface.co/prem-research/Premonition-Exp/resolve/main/demo/premonition-enterprise.mp4).
|
| 27 |
|
| 28 |
+
The silent walkthrough records actual API calls using fictional business scenarios: a purchase policy, invoice routing, a schematic warehouse handoff, customer voicemail and a combined evidence packet. The accompanying fixtures and replay script are included in this repository.
|
| 29 |
|
| 30 |
## Install the serving environment
|
| 31 |
|
demo/premonition-enterprise.mp4
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:1db743810d2254c9b0527b3a37b79f44acd4d87539f17d741a3dac8707407655
|
| 3 |
+
size 3435614
|