Instructions to use zachtheyek/aetherscan with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use zachtheyek/aetherscan with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://zachtheyek/aetherscan") - Notebooks
- Google Colab
- Kaggle
| { | |
| "db": { | |
| "get_connection_timeout": 60.0, | |
| "stop_writer_timeout": 10.0, | |
| "write_interval": 5.0, | |
| "write_buffer_max_size": 5000, | |
| "write_retry_delay": 1.0, | |
| "flush_timeout": 10.0, | |
| "bulk_chunk_rows": 50000, | |
| "bulk_queue_max_items": 32, | |
| "stop_drain_timeout": 600.0 | |
| }, | |
| "manager": { | |
| "n_processes": 96, | |
| "chunks_per_worker": 4, | |
| "pool_terminate_timeout": 10.0 | |
| }, | |
| "monitor": { | |
| "get_gpu_timeout": 5.0, | |
| "stop_monitor_timeout": 10.0, | |
| "monitor_interval": 1.0, | |
| "monitor_retry_delay": 1.0, | |
| "annotate_stages": true, | |
| "dashboard_enabled": true, | |
| "dashboard_port": 8501, | |
| "benchmark_report_enabled": true | |
| }, | |
| "logger": { | |
| "console_level": "INFO", | |
| "file_level": "INFO", | |
| "slack_level": "INFO", | |
| "slack_enabled": true, | |
| "slack_channel": null, | |
| "slack_username": "Aetherscan", | |
| "slack_timeout": 15.0, | |
| "slack_retry_attempts": 3, | |
| "slack_buffer_size": 100, | |
| "slack_flush_interval": 60.0, | |
| "slack_broadcast_level": "ERROR" | |
| }, | |
| "beta_vae": { | |
| "latent_dim": 8, | |
| "dense_layer_size": 512, | |
| "kernel_size": [ | |
| 3, | |
| 3 | |
| ], | |
| "beta": 1.5, | |
| "alpha": 10.0, | |
| "mixed_precision": false, | |
| "regularization_active": false | |
| }, | |
| "reproducibility": { | |
| "seed": 11, | |
| "tf_deterministic_ops": true, | |
| "derived_rf_seed": 961975133 | |
| }, | |
| "rf": { | |
| "n_estimators": 1000, | |
| "bootstrap": true, | |
| "max_features": "sqrt", | |
| "n_jobs": -1, | |
| "seed": null, | |
| "latent_variant": "z_mean", | |
| "active_dims": [ | |
| 0, | |
| 1, | |
| 2, | |
| 3, | |
| 4, | |
| 5, | |
| 6, | |
| 7 | |
| ], | |
| "z_aug_draws": 4, | |
| "active_units_threshold": 0.01, | |
| "selection_max_fpr": 0.01, | |
| "selection_bootstrap_rounds": 500, | |
| "max_ece": 0.05, | |
| "calibration_min_isotonic": 1000, | |
| "calibration_active": false, | |
| "calibration_method": null, | |
| "val_selection_fraction": 0.5, | |
| "val_calibration_fraction": 0.25, | |
| "screen_recall_tolerance": 0.0 | |
| }, | |
| "gpu": { | |
| "num_replicas": null, | |
| "per_gpu_memory_limit_mb": null, | |
| "nccl_num_packs": 2, | |
| "use_async_allocator": true, | |
| "gpu_thread_mode": "gpu_private", | |
| "gpu_thread_count": 2 | |
| }, | |
| "data": { | |
| "num_observations": 6, | |
| "width_bin": 4096, | |
| "downsample_factor": 8, | |
| "time_bins": 16, | |
| "freq_resolution": 2.7939677238464355, | |
| "time_resolution": 18.25361108, | |
| "num_target_backgrounds": 45000, | |
| "background_load_chunk_size": 15000, | |
| "max_chunks_per_file": 1, | |
| "inference_background_load_chunk_size": 50000 | |
| }, | |
| "training": { | |
| "num_training_rounds": 10, | |
| "epochs_per_round": 100, | |
| "posterior_collapse_kl_epsilon": 0.01, | |
| "min_active_units_fraction": 0.5, | |
| "posterior_collapse_patience": 5, | |
| "num_samples_beta_vae": 499200, | |
| "num_samples_rf": 99840, | |
| "train_val_split": 0.8, | |
| "per_replica_batch_size": 128, | |
| "effective_batch_size": 7680, | |
| "per_replica_val_batch_size": 64, | |
| "signal_injection_chunk_size": 50000, | |
| "data_gen_task_size": 64, | |
| "round_array_dtype": "float16", | |
| "round_data_dir": null, | |
| "overlap_data_generation": true, | |
| "keep_round_data": true, | |
| "plot_injection_subsampling_count": 100000, | |
| "plot_injection_outlier_percentile": 99.0, | |
| "latent_viz_num_cadences_per_type": 960, | |
| "latent_viz_step_interval": 10, | |
| "latent_viz_umap_fit_max_samples": 100000, | |
| "latent_viz_umap_n_neighbors": [ | |
| 5, | |
| 15, | |
| 50 | |
| ], | |
| "latent_viz_umap_min_dist": [ | |
| 0.0, | |
| 0.1, | |
| 0.5 | |
| ], | |
| "latent_viz_gif_max_frames": 500, | |
| "latent_viz_gif_duration_ms": 100, | |
| "latent_traversal_every_round": false, | |
| "latent_traversal_num_steps": 7, | |
| "latent_traversal_max_sigma": 3.0, | |
| "shap_max_samples_summary": 5000, | |
| "shap_max_samples_interaction": 1500, | |
| "shap_top_k_features_dependence": 48, | |
| "rf_decision_boundary_grid_size": 150, | |
| "rf_decision_boundary_max_points": 5000, | |
| "min_val_auc": 0.0, | |
| "snr_base": 10, | |
| "initial_snr_range": 40, | |
| "final_snr_range": 10, | |
| "curriculum_schedule": "exponential", | |
| "exponential_decay_rate": -3.0, | |
| "step_easy_rounds": 5, | |
| "step_hard_rounds": 15, | |
| "base_learning_rate": 0.001, | |
| "min_learning_rate": 1e-06, | |
| "min_pct_improvement": 0.001, | |
| "patience_threshold": 3, | |
| "reduction_factor": 0.2, | |
| "max_retries": 3, | |
| "retry_delay": 60 | |
| }, | |
| "inference": { | |
| "per_replica_batch_size": 2048, | |
| "classification_threshold": 0.99, | |
| "screening_threshold": 0.5, | |
| "mc_draws": 32, | |
| "reference_cloud_size": 10000, | |
| "cadence_group_by_cols": [ | |
| "Target", | |
| "Session", | |
| "Band", | |
| "Cadence ID", | |
| "Frequency" | |
| ], | |
| "cadence_h5_path_col": ".h5 path", | |
| "cadence_expected_obs": 6, | |
| "coarse_channel_width": 1048576, | |
| "coarse_channel_log_interval": null, | |
| "bandpass_method": "pfb", | |
| "pfb_taps_per_channel": 12, | |
| "bandpass_debug_plot": false, | |
| "spline_order": 16, | |
| "detection_window_size": 256, | |
| "detection_step_size": 128, | |
| "stat_threshold": 2048.0, | |
| "stamp_width": 4096, | |
| "store_downsampled_stamps": true, | |
| "overlap_search": true, | |
| "overlap_fraction": 0.5, | |
| "discard_side_channels": false, | |
| "side_channel_count": 0, | |
| "inference_viz_enabled": true, | |
| "stamp_gallery_top_k": 12, | |
| "max_candidate_plots": 50, | |
| "max_retries": 3, | |
| "retry_delay": 60 | |
| }, | |
| "hf": { | |
| "repo_id": "zachtheyek/aetherscan", | |
| "upload_after_training": true, | |
| "revision": null | |
| }, | |
| "checkpoint": { | |
| "load_tag": null, | |
| "start_round": 1, | |
| "save_tag": "train_20260729_152426", | |
| "force_tag": false | |
| } | |
| } |