Instructions to use vikp/texify2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vikp/texify2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="vikp/texify2")# Load model directly from transformers import AutoTokenizer, AutoModelForImageTextToText tokenizer = AutoTokenizer.from_pretrained("vikp/texify2") model = AutoModelForImageTextToText.from_pretrained("vikp/texify2") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use vikp/texify2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "vikp/texify2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "vikp/texify2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/vikp/texify2
- SGLang
How to use vikp/texify2 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 "vikp/texify2" \ --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": "vikp/texify2", "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 "vikp/texify2" \ --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": "vikp/texify2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use vikp/texify2 with Docker Model Runner:
docker model run hf.co/vikp/texify2
File size: 617 Bytes
6350938 | 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 34 35 36 37 | {
"do_align_long_axis": false,
"do_normalize": false,
"do_pad": false,
"do_rescale": false,
"do_resize": false,
"do_thumbnail": false,
"feature_extractor_type": "DonutFeatureExtractor",
"image_mean": [
0.485,
0.456,
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],
"image_processor_type": "VariableDonutImageProcessor",
"image_std": [
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],
"max_size": {
"height": 420,
"width": 420
},
"patch_size": [
4,
4
],
"processor_class": "VariableDonutProcessor",
"resample": 2,
"rescale_factor": 0.00392156862745098,
"size": [
420,
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],
"train": false
}
|