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bollscoasts/pix2act-onnx
pix2act-onnx is a image-text-to-text model from bollscoasts. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
ONNX export of google/pix2struct-base for GUI automation via Transformers.js/WebGPU.
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From the Hugging Face model README
ONNX export of google/pix2struct-base for GUI automation via Transformers.js/WebGPU.
| Property | Value |
|---|---|
| Original Model | google/pix2struct-base |
| Architecture | Pix2Struct (Vision2Seq) |
| Parameters | ~282M |
| Export Format | ONNX (opset 17) |
| Quantization | INT8 dynamic |
| Browser Eligible | Yes |
Pix2Struct is a pretrained image-to-text model designed for understanding visually situated language. It uses a pixel-only approach making it ideal for:
import onnxruntime as ort
from transformers import AutoProcessor
from PIL import Image
# Load processor
processor = AutoProcessor.from_pretrained("google/pix2struct-base")
# Load ONNX model
session = ort.InferenceSession("encoder_model.onnx")
# Process image
image = Image.open("screenshot.png")
inputs = processor(images=image, return_tensors="np")
# Run inference
outputs = session.run(None, dict(inputs))
import { pipeline } from "@xenova/transformers";
// Load the ONNX model
const pipe = await pipeline("image-to-text", "bollscoasts/pix2act-onnx");
// Run inference on screenshot
const result = await pipe(image);
console.log(result);
Exported using HotelBench ONNX export utilities.
hotelbench export-onnx pix2act -o models/pix2act-onnx --quantize
Apache 2.0