Download example.py from tyxqiean/QIME: direct link, hf CLI and curl.
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https://huggingface.co/tyxqiean/QIME/resolve/main/example.py
- Command line
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hf download hf://tyxqiean/QIME/example.py
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curl -L -o example.py https://huggingface.co/tyxqiean/QIME/resolve/main/example.py
1.38 kB
| """Run from the downloaded release: python example.py [--device cuda:0].""" | |
| import argparse | |
| import sys | |
| from pathlib import Path | |
| import numpy as np | |
| # HF snapshots use symlinks; retain the snapshot directory for sibling imports. | |
| sys.path.insert(0, str(Path(__file__).absolute().parent)) | |
| from qime import QIMEModel | |
| def main(): | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument("--device", default=None) | |
| parser.add_argument("--local-files-only", action="store_true") | |
| args = parser.parse_args() | |
| model = QIMEModel.from_pretrained( | |
| Path(__file__).parent, device=args.device, local_files_only=args.local_files_only, | |
| ) | |
| texts = [ | |
| "Patient presents with severe chest pain.", | |
| "Treatment involves daily insulin injections.", | |
| ] | |
| embeddings = model.encode(texts) | |
| assert embeddings.shape == (2, 8855) | |
| assert np.all(embeddings.sum(axis=1) == 256) | |
| assert np.isin(embeddings, [0, 1]).all() | |
| print("Embedding shape:", embeddings.shape) | |
| print("Active dimensions per text:", embeddings.sum(axis=1)) | |
| for text, embedding in zip(texts, embeddings): | |
| print("\nText:", text) | |
| print("First 10 active coordinates (coordinate order, not relevance order):") | |
| for index in np.flatnonzero(embedding)[:10]: | |
| print(f"[{index}] {model.questions[index]}") | |
| if __name__ == "__main__": | |
| main() | |