Image-Text-to-Text
Transformers
Safetensors
interfaze_lite
feature-extraction
vlm
any-to-text
audio-text-to-text
multimodal
multilingual
mixture-of-architectures
ocr
document-understanding
speech-recognition
speaker-diarization
object-detection
gui-grounding
image-segmentation
translation
time-series-forecasting
guardrails
structured-output
agent
custom_code
Instructions to use interfaze-ai/interfaze-1-lite with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use interfaze-ai/interfaze-1-lite with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="interfaze-ai/interfaze-1-lite", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("interfaze-ai/interfaze-1-lite", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use interfaze-ai/interfaze-1-lite with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "interfaze-ai/interfaze-1-lite" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "interfaze-ai/interfaze-1-lite", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/interfaze-ai/interfaze-1-lite
- SGLang
How to use interfaze-ai/interfaze-1-lite 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 "interfaze-ai/interfaze-1-lite" \ --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": "interfaze-ai/interfaze-1-lite", "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 "interfaze-ai/interfaze-1-lite" \ --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": "interfaze-ai/interfaze-1-lite", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use interfaze-ai/interfaze-1-lite with Docker Model Runner:
docker model run hf.co/interfaze-ai/interfaze-1-lite
Download requirements.txt from interfaze-ai/interfaze-1-lite: direct link, hf CLI and curl.
- Browser
- Download file 527 Bytes
-
https://huggingface.co/interfaze-ai/interfaze-1-lite/resolve/main/requirements.txt
- Command line
-
hf download hf://interfaze-ai/interfaze-1-lite/requirements.txt
-
curl -L -o requirements.txt https://huggingface.co/interfaze-ai/interfaze-1-lite/resolve/main/requirements.txt
527 Bytes
| transformers==5.15.0 | |
| accelerate==1.15.0 | |
| torch==2.13.0 | |
| torchvision==0.28.0 | |
| pillow==12.3.0 | |
| numpy==2.3.5 | |
| soundfile==0.14.0 | |
| httpx==0.28.1 | |
| rapidfuzz==3.14.6 | |
| pymupdf==1.28.2 | |
| opencv-python-headless==5.0.0.93 | |
| paddlepaddle==3.2.2 | |
| paddleocr==3.3.2 | |
| pyannote.audio==4.0.7 | |
| flash-linear-attention==0.5.2 | |
| kernels==0.16.2 | |
| pandas==3.0.6 | |
| sam-2 @ git+https://github.com/facebookresearch/sam2.git@2b90b9f5ceec907a1c18123530e92e794ad901a4 | |
| timesfm[torch] @ git+https://github.com/google-research/timesfm.git@bf88c5dc88f6275b7071ebcd9051406c11435c0c | |