nanigock/paw-interpreter-onnx

paw-interpreter-onnx

ONNX runtime models for ProgramAsWeights.

Model Files

Core (always downloaded):

• text_embeddings.onnx - Text tokenizer embeddings
• interpreter.onnx - Main interpreter model
• tokenizer/ - Fast tokenizer

Optional (lazy loaded):

• image_encoder.onnx - Image encoder (CLIP + projection) - only downloaded when using image inputs

Usage

import programasweights as paw

# Text-only program (no Pillow needed!)
fn = paw.function("abc123")
result = fn("Extract emails: contact@example.com")

# With images (requires: pip install programasweights[images])
from PIL import Image
img = Image.open("photo.jpg")
result = fn("Count apples:", img)

Installation

# Base install (text-only, ~70MB)
pip install programasweights

# With image support (~85MB)
pip install programasweights[images]

Model Details

• Base model: Qwen2-0.5B
• Runtime: ONNX (lightweight, fast)
• Input: .paw files (prefix KV cache)
• Output: Generated text