Instructions to use pragadeeshv23/arm-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use pragadeeshv23/arm-model with TF-Keras:
# Note: 'keras<3.x' or 'tf_keras' must be installed (legacy) # See https://github.com/keras-team/tf-keras for more details. from huggingface_hub import from_pretrained_keras model = from_pretrained_keras("pragadeeshv23/arm-model") - Notebooks
- Google Colab
- Kaggle
File size: 578 Bytes
5b86813 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | #!/usr/bin/env python3
from pathlib import Path
# Check path fix
config_OUTPUT_DIR = Path("road-anomaly-detection")
timestamp = "20260124_164145"
run_name = f"train_{timestamp}"
# New way (fixed)
run_dir_new = Path("runs/detect") / config_OUTPUT_DIR / run_name
best_model_new = run_dir_new / "weights" / "best.pt"
print("NEW PATH (fixed):", best_model_new)
print("NEW PATH exists:", best_model_new.exists())
# Check actual path
actual_path = Path("runs/detect/road-anomaly-detection/train_20260124_164145/weights/best.pt")
print("Actual path exists:", actual_path.exists())
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