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Deploy merged demo: representative images (#42), t-SNE exact solver (#45), PCA reproducibility (#46), decoupled projection/KMeans + thread pipeline, demo header/footer
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def list_available_models():
"""List all available models."""
# Create list of all models
models_data = []
# Add special models first (Imageomics BioCLIP family)
models_data.extend([
{"name": "hf-hub:imageomics/bioclip-2", "pretrained": None},
{"name": "hf-hub:imageomics/bioclip-2.5-vith14", "pretrained": None},
{"name": "hf-hub:imageomics/biocap", "pretrained": None},
{"name": "hf-hub:imageomics/bioclip", "pretrained": None}
])
# OpenCLIP models
import open_clip
openclip_models = open_clip.list_pretrained()
for model_name, pretrained in openclip_models:
models_data.append({
"name": model_name,
"pretrained": pretrained
})
return models_data
def print_available_models():
"""CLI entry point: print all available models to stdout."""
models = list_available_models()
for m in models:
if m["pretrained"]:
print(f"{m['name']} (pretrained: {m['pretrained']})")
else:
print(m["name"])