Instructions to use yuchenxie/Arlow-Vision-Encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yuchenxie/Arlow-Vision-Encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="yuchenxie/Arlow-Vision-Encoder")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("yuchenxie/Arlow-Vision-Encoder", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use yuchenxie/Arlow-Vision-Encoder with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "yuchenxie/Arlow-Vision-Encoder" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "yuchenxie/Arlow-Vision-Encoder", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/yuchenxie/Arlow-Vision-Encoder
- SGLang
How to use yuchenxie/Arlow-Vision-Encoder 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 "yuchenxie/Arlow-Vision-Encoder" \ --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": "yuchenxie/Arlow-Vision-Encoder", "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 "yuchenxie/Arlow-Vision-Encoder" \ --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": "yuchenxie/Arlow-Vision-Encoder", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use yuchenxie/Arlow-Vision-Encoder with Docker Model Runner:
docker model run hf.co/yuchenxie/Arlow-Vision-Encoder
File size: 631 Bytes
49d4668 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 | {
"do_convert_rgb": true,
"do_normalize": true,
"do_pan_and_scan": false,
"do_rescale": true,
"do_resize": true,
"image_mean": [
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0.5
],
"image_processor_type": "ArlowImageProcessor",
"image_std": [
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"max_pixels": 1003520,
"merge_size": 2,
"min_pixels": 3136,
"pan_and_scan_max_num_crops": 4,
"pan_and_scan_min_crop_size": 256,
"pan_and_scan_min_ratio_to_activate": 1.6,
"patch_size": 14,
"resample": 3,
"rescale_factor": 0.00392156862745098,
"size": {
"longest_edge": 1003520,
"shortest_edge": 3136
},
"temporal_patch_size": 2
}
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