Image-Text-to-Text
Transformers
Safetensors
OpenVINO
English
gemma3
vision-language
multimodal
home-security
smart-home
on-device
openvino-export
text-generation-inference
Instructions to use fischju/glimpse-v1-openvino with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fischju/glimpse-v1-openvino with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="fischju/glimpse-v1-openvino")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("fischju/glimpse-v1-openvino") model = AutoModelForMultimodalLM.from_pretrained("fischju/glimpse-v1-openvino") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use fischju/glimpse-v1-openvino with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "fischju/glimpse-v1-openvino" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "fischju/glimpse-v1-openvino", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/fischju/glimpse-v1-openvino
- SGLang
How to use fischju/glimpse-v1-openvino 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 "fischju/glimpse-v1-openvino" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "fischju/glimpse-v1-openvino", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "fischju/glimpse-v1-openvino" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "fischju/glimpse-v1-openvino", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use fischju/glimpse-v1-openvino with Docker Model Runner:
docker model run hf.co/fischju/glimpse-v1-openvino
This model was converted to OpenVINO from llmvision/glimpse-v1 using optimum-intel
via the export space.
First make sure you have optimum-intel installed:
pip install optimum[openvino]
To load your model you can do as follows:
from optimum.intel import OVModelForVisualCausalLM
model_id = "fischju/glimpse-v1-openvino"
model = OVModelForVisualCausalLM.from_pretrained(model_id)
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