Instructions to use LEAP-LAB-KUS/jevkt-checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use LEAP-LAB-KUS/jevkt-checkpoints with PEFT:
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- Notebooks
- Google Colab
- Kaggle
pod backup 2026-11-07: pykt (2000-2400)
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- pykt/dbe_kt22/coldstart/pykt-sparsekt-csN8-s0/train_info.json.done +1 -0
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- pykt/dbe_kt22/coldstart/pykt-sparsekt-csNall-s0/train_info.json.done +1 -0
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- pykt/dbe_kt22/coldstart/pykt-sparsekt-csNall-s3/train_info.json.done +1 -0
- pykt/dbe_kt22/coldstart/pykt-sparsekt-csNall-s4/train_info.json.done +1 -0
- pykt/dbe_kt22/coldstart/pykt-stablekt-csN128-s0/train_info.json.done +1 -0
- pykt/dbe_kt22/coldstart/pykt-stablekt-csN128-s1/train_info.json.done +1 -0
- pykt/dbe_kt22/coldstart/pykt-stablekt-csN128-s2/train_info.json.done +1 -0
- pykt/dbe_kt22/coldstart/pykt-stablekt-csN128-s3/train_info.json.done +1 -0
- pykt/dbe_kt22/coldstart/pykt-stablekt-csN128-s4/train_info.json.done +1 -0
- pykt/dbe_kt22/coldstart/pykt-stablekt-csN16-s0/train_info.json.done +1 -0
- pykt/dbe_kt22/coldstart/pykt-stablekt-csN16-s1/train_info.json.done +1 -0
- pykt/dbe_kt22/coldstart/pykt-stablekt-csN16-s2/train_info.json.done +1 -0
- pykt/dbe_kt22/coldstart/pykt-stablekt-csN16-s3/train_info.json.done +1 -0
- pykt/dbe_kt22/coldstart/pykt-stablekt-csN16-s4/train_info.json.done +1 -0
- pykt/dbe_kt22/coldstart/pykt-stablekt-csN256-s0/train_info.json.done +1 -0
- pykt/dbe_kt22/coldstart/pykt-stablekt-csN256-s1/train_info.json.done +1 -0
- pykt/dbe_kt22/coldstart/pykt-stablekt-csN256-s2/train_info.json.done +1 -0
- pykt/dbe_kt22/coldstart/pykt-stablekt-csN256-s3/train_info.json.done +1 -0
- pykt/dbe_kt22/coldstart/pykt-stablekt-csN256-s4/train_info.json.done +1 -0
- pykt/dbe_kt22/coldstart/pykt-stablekt-csN32-s0/train_info.json.done +1 -0
- pykt/dbe_kt22/coldstart/pykt-stablekt-csN32-s1/train_info.json.done +1 -0
- pykt/dbe_kt22/coldstart/pykt-stablekt-csN32-s2/train_info.json.done +1 -0
- pykt/dbe_kt22/coldstart/pykt-stablekt-csN32-s3/train_info.json.done +1 -0
- pykt/dbe_kt22/coldstart/pykt-stablekt-csN32-s4/train_info.json.done +1 -0
- pykt/dbe_kt22/coldstart/pykt-stablekt-csN64-s0/train_info.json.done +1 -0
- pykt/dbe_kt22/coldstart/pykt-stablekt-csN64-s1/train_info.json.done +1 -0
- pykt/dbe_kt22/coldstart/pykt-stablekt-csN64-s2/train_info.json.done +1 -0
- pykt/dbe_kt22/coldstart/pykt-stablekt-csN64-s3/train_info.json.done +1 -0
- pykt/dbe_kt22/coldstart/pykt-stablekt-csN64-s4/train_info.json.done +1 -0
- pykt/dbe_kt22/coldstart/pykt-stablekt-csN8-s0/train_info.json.done +1 -0
- pykt/dbe_kt22/coldstart/pykt-stablekt-csN8-s1/train_info.json.done +1 -0
- pykt/dbe_kt22/coldstart/pykt-stablekt-csN8-s2/train_info.json.done +1 -0
- pykt/dbe_kt22/coldstart/pykt-stablekt-csN8-s3/train_info.json.done +1 -0
- pykt/dbe_kt22/coldstart/pykt-stablekt-csN8-s4/train_info.json.done +1 -0
- pykt/dbe_kt22/coldstart/pykt-stablekt-csNall-s0/train_info.json.done +1 -0
- pykt/dbe_kt22/coldstart/pykt-stablekt-csNall-s1/train_info.json.done +1 -0
- pykt/dbe_kt22/coldstart/pykt-stablekt-csNall-s2/train_info.json.done +1 -0
- pykt/dbe_kt22/coldstart/pykt-stablekt-csNall-s3/train_info.json.done +1 -0
- pykt/dbe_kt22/coldstart/pykt-stablekt-csNall-s4/train_info.json.done +1 -0
- pykt/dbe_kt22/pykt-atdkt-s1/qid_model.ckpt +3 -0
- pykt/dbe_kt22/pykt-atdkt-s1/train_info.json +1 -0
- pykt/dbe_kt22/pykt-atdkt-s2/qid_model.ckpt +3 -0
- pykt/dbe_kt22/pykt-atdkt-s2/train_info.json +1 -0
- pykt/dbe_kt22/pykt-atktfix-s1/qid_model.ckpt +3 -0
pykt/dbe_kt22/coldstart/pykt-sparsekt-csN8-s0/train_info.json.done
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{"train_s": 13.6, "epochs": 18, "best_epoch": 8, "dev_auc_pykt": 0.7193431568431568, "n_train_users": 6, "n_train_chunks": 11, "n_dev_chunks": 3, "batch_size": 64, "seq_len": 200, "n_val_users": 2, "score_s": 130.7, "flip_max_diff": 0.0, "peak_gb": 0.54}
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pykt/dbe_kt22/coldstart/pykt-sparsekt-csN8-s1/train_info.json.done
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{"train_s": 0.8, "epochs": 15, "best_epoch": 5, "dev_auc_pykt": 0.6116300366300367, "n_train_users": 6, "n_train_chunks": 10, "n_dev_chunks": 4, "batch_size": 64, "seq_len": 200, "n_val_users": 2, "score_s": 4.6, "flip_max_diff": 0.0, "peak_gb": 0.54}
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pykt/dbe_kt22/coldstart/pykt-sparsekt-csN8-s2/train_info.json.done
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{"train_s": 2.7, "epochs": 27, "best_epoch": 17, "dev_auc_pykt": 0.7202182759896412, "n_train_users": 6, "n_train_chunks": 9, "n_dev_chunks": 5, "batch_size": 64, "seq_len": 200, "n_val_users": 2, "score_s": 7.6, "flip_max_diff": 0.0, "peak_gb": 0.59}
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pykt/dbe_kt22/coldstart/pykt-sparsekt-csN8-s3/train_info.json.done
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{"train_s": 5.9, "epochs": 77, "best_epoch": 67, "dev_auc_pykt": 0.6924448974391642, "n_train_users": 6, "n_train_chunks": 10, "n_dev_chunks": 3, "batch_size": 64, "seq_len": 200, "n_val_users": 2, "score_s": 6.2, "flip_max_diff": 0.0, "peak_gb": 0.55}
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pykt/dbe_kt22/coldstart/pykt-sparsekt-csN8-s4/train_info.json.done
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{"train_s": 8.4, "epochs": 45, "best_epoch": 35, "dev_auc_pykt": 0.7439374372219831, "n_train_users": 6, "n_train_chunks": 11, "n_dev_chunks": 5, "batch_size": 64, "seq_len": 200, "n_val_users": 2, "score_s": 7.0, "flip_max_diff": 0.0, "peak_gb": 0.55}
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{"train_s": 90.3, "epochs": 63, "best_epoch": 53, "dev_auc_pykt": 0.7913628748991568, "n_train_users": 655, "n_train_chunks": 1144, "n_dev_chunks": 291, "batch_size": 64, "seq_len": 200, "n_val_users": 164, "score_s": 7.2, "flip_max_diff": 0.0, "peak_gb": 0.83}
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{"train_s": 99.3, "epochs": 70, "best_epoch": 60, "dev_auc_pykt": 0.7870684831773451, "n_train_users": 655, "n_train_chunks": 1154, "n_dev_chunks": 281, "batch_size": 64, "seq_len": 200, "n_val_users": 164, "score_s": 8.6, "flip_max_diff": 0.0, "peak_gb": 0.88}
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{"train_s": 96.8, "epochs": 66, "best_epoch": 56, "dev_auc_pykt": 0.8005655898039881, "n_train_users": 655, "n_train_chunks": 1150, "n_dev_chunks": 285, "batch_size": 64, "seq_len": 200, "n_val_users": 164, "score_s": 7.4, "flip_max_diff": 0.0, "peak_gb": 0.83}
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{"train_s": 84.7, "epochs": 58, "best_epoch": 48, "dev_auc_pykt": 0.7903939001171476, "n_train_users": 655, "n_train_chunks": 1143, "n_dev_chunks": 292, "batch_size": 64, "seq_len": 200, "n_val_users": 164, "score_s": 7.9, "flip_max_diff": 0.0, "peak_gb": 0.84}
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{"train_s": 7.3, "epochs": 15, "best_epoch": 5, "dev_auc_pykt": 0.6690056181030373, "n_train_users": 102, "n_train_chunks": 172, "n_dev_chunks": 46, "batch_size": 64, "seq_len": 200, "n_val_users": 26, "score_s": 9.8, "flip_max_diff": 0.0, "peak_gb": 2.92}
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{"train_s": 41.0, "epochs": 76, "best_epoch": 66, "dev_auc_pykt": 0.7868452961414554, "n_train_users": 102, "n_train_chunks": 180, "n_dev_chunks": 48, "batch_size": 64, "seq_len": 200, "n_val_users": 26, "score_s": 12.0, "flip_max_diff": 0.0, "peak_gb": 2.92}
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{"train_s": 35.9, "epochs": 58, "best_epoch": 48, "dev_auc_pykt": 0.7332969072049063, "n_train_users": 102, "n_train_chunks": 180, "n_dev_chunks": 46, "batch_size": 64, "seq_len": 200, "n_val_users": 26, "score_s": 10.5, "flip_max_diff": 0.0, "peak_gb": 2.93}
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{"train_s": 11.2, "epochs": 20, "best_epoch": 10, "dev_auc_pykt": 0.695081106322755, "n_train_users": 102, "n_train_chunks": 177, "n_dev_chunks": 46, "batch_size": 64, "seq_len": 200, "n_val_users": 26, "score_s": 10.2, "flip_max_diff": 0.0, "peak_gb": 2.93}
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{"train_s": 8.3, "epochs": 29, "best_epoch": 19, "dev_auc_pykt": 0.7008169934640524, "n_train_users": 13, "n_train_chunks": 24, "n_dev_chunks": 5, "batch_size": 64, "seq_len": 200, "n_val_users": 3, "score_s": 17.5, "flip_max_diff": 0.0, "peak_gb": 1.19}
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{"train_s": 5.1, "epochs": 33, "best_epoch": 23, "dev_auc_pykt": 0.6171694764862466, "n_train_users": 13, "n_train_chunks": 21, "n_dev_chunks": 5, "batch_size": 64, "seq_len": 200, "n_val_users": 3, "score_s": 8.0, "flip_max_diff": 0.0, "peak_gb": 1.06}
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{"train_s": 5.7, "epochs": 36, "best_epoch": 26, "dev_auc_pykt": 0.7443750000000001, "n_train_users": 13, "n_train_chunks": 22, "n_dev_chunks": 6, "batch_size": 64, "seq_len": 200, "n_val_users": 3, "score_s": 11.2, "flip_max_diff": 0.0, "peak_gb": 1.11}
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{"train_s": 3.6, "epochs": 22, "best_epoch": 12, "dev_auc_pykt": 0.7320574162679426, "n_train_users": 13, "n_train_chunks": 23, "n_dev_chunks": 4, "batch_size": 64, "seq_len": 200, "n_val_users": 3, "score_s": 11.0, "flip_max_diff": 0.0, "peak_gb": 1.15}
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{"train_s": 21.3, "epochs": 100, "best_epoch": 90, "dev_auc_pykt": 0.6744213791457886, "n_train_users": 13, "n_train_chunks": 25, "n_dev_chunks": 4, "batch_size": 64, "seq_len": 200, "n_val_users": 3, "score_s": 10.3, "flip_max_diff": 0.0, "peak_gb": 1.24}
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{"train_s": 49.3, "epochs": 43, "best_epoch": 33, "dev_auc_pykt": 0.7712472727389844, "n_train_users": 205, "n_train_chunks": 361, "n_dev_chunks": 92, "batch_size": 64, "seq_len": 200, "n_val_users": 51, "score_s": 12.3, "flip_max_diff": 0.0, "peak_gb": 2.97}
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{"train_s": 52.6, "epochs": 48, "best_epoch": 38, "dev_auc_pykt": 0.7688287007825758, "n_train_users": 205, "n_train_chunks": 351, "n_dev_chunks": 90, "batch_size": 64, "seq_len": 200, "n_val_users": 51, "score_s": 11.0, "flip_max_diff": 0.0, "peak_gb": 2.92}
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{"train_s": 69.7, "epochs": 60, "best_epoch": 50, "dev_auc_pykt": 0.7620187525927259, "n_train_users": 205, "n_train_chunks": 369, "n_dev_chunks": 98, "batch_size": 64, "seq_len": 200, "n_val_users": 51, "score_s": 12.6, "flip_max_diff": 0.0, "peak_gb": 2.94}
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{"train_s": 60.5, "epochs": 53, "best_epoch": 43, "dev_auc_pykt": 0.7586867008596403, "n_train_users": 205, "n_train_chunks": 363, "n_dev_chunks": 89, "batch_size": 64, "seq_len": 200, "n_val_users": 51, "score_s": 11.0, "flip_max_diff": 0.0, "peak_gb": 2.92}
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{"train_s": 58.5, "epochs": 50, "best_epoch": 40, "dev_auc_pykt": 0.7708705053924607, "n_train_users": 205, "n_train_chunks": 357, "n_dev_chunks": 91, "batch_size": 64, "seq_len": 200, "n_val_users": 51, "score_s": 10.5, "flip_max_diff": 0.0, "peak_gb": 2.92}
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{"train_s": 14.8, "epochs": 43, "best_epoch": 33, "dev_auc_pykt": 0.7031047446201713, "n_train_users": 26, "n_train_chunks": 48, "n_dev_chunks": 9, "batch_size": 64, "seq_len": 200, "n_val_users": 6, "score_s": 17.1, "flip_max_diff": 0.0, "peak_gb": 2.23}
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{"train_s": 10.2, "epochs": 57, "best_epoch": 47, "dev_auc_pykt": 0.7275566139468009, "n_train_users": 26, "n_train_chunks": 43, "n_dev_chunks": 9, "batch_size": 64, "seq_len": 200, "n_val_users": 6, "score_s": 10.2, "flip_max_diff": 0.0, "peak_gb": 2.06}
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{"train_s": 7.3, "epochs": 33, "best_epoch": 23, "dev_auc_pykt": 0.6777992243004204, "n_train_users": 26, "n_train_chunks": 46, "n_dev_chunks": 9, "batch_size": 64, "seq_len": 200, "n_val_users": 6, "score_s": 11.2, "flip_max_diff": 0.0, "peak_gb": 2.18}
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{"train_s": 5.9, "epochs": 35, "best_epoch": 25, "dev_auc_pykt": 0.6838479233826797, "n_train_users": 26, "n_train_chunks": 45, "n_dev_chunks": 11, "batch_size": 64, "seq_len": 200, "n_val_users": 6, "score_s": 11.8, "flip_max_diff": 0.0, "peak_gb": 2.13}
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|
pykt/dbe_kt22/coldstart/pykt-stablekt-csN64-s0/train_info.json.done
ADDED
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pykt/dbe_kt22/coldstart/pykt-stablekt-csN64-s1/train_info.json.done
ADDED
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|
pykt/dbe_kt22/coldstart/pykt-stablekt-csN64-s2/train_info.json.done
ADDED
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|
pykt/dbe_kt22/coldstart/pykt-stablekt-csN64-s3/train_info.json.done
ADDED
|
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|
pykt/dbe_kt22/coldstart/pykt-stablekt-csN64-s4/train_info.json.done
ADDED
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|
pykt/dbe_kt22/coldstart/pykt-stablekt-csN8-s0/train_info.json.done
ADDED
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|
pykt/dbe_kt22/coldstart/pykt-stablekt-csN8-s1/train_info.json.done
ADDED
|
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|
pykt/dbe_kt22/coldstart/pykt-stablekt-csN8-s2/train_info.json.done
ADDED
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|
pykt/dbe_kt22/coldstart/pykt-stablekt-csN8-s3/train_info.json.done
ADDED
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|
pykt/dbe_kt22/coldstart/pykt-stablekt-csN8-s4/train_info.json.done
ADDED
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| 1 |
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|
pykt/dbe_kt22/coldstart/pykt-stablekt-csNall-s0/train_info.json.done
ADDED
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| 1 |
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|
pykt/dbe_kt22/coldstart/pykt-stablekt-csNall-s1/train_info.json.done
ADDED
|
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|
pykt/dbe_kt22/coldstart/pykt-stablekt-csNall-s2/train_info.json.done
ADDED
|
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|
pykt/dbe_kt22/coldstart/pykt-stablekt-csNall-s3/train_info.json.done
ADDED
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|
pykt/dbe_kt22/coldstart/pykt-stablekt-csNall-s4/train_info.json.done
ADDED
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|
pykt/dbe_kt22/pykt-atdkt-s1/qid_model.ckpt
ADDED
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|
pykt/dbe_kt22/pykt-atdkt-s2/qid_model.ckpt
ADDED
|
@@ -0,0 +1,3 @@
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| 1 |
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size 3352941
|
pykt/dbe_kt22/pykt-atdkt-s2/train_info.json
ADDED
|
@@ -0,0 +1 @@
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|
|
|
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|
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| 1 |
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pykt/dbe_kt22/pykt-atktfix-s1/qid_model.ckpt
ADDED
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@@ -0,0 +1,3 @@
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| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:2ea0ee893c88ff12391c0972cbcb434f1cedbadfef15e2976ed4d782c0608d1a
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| 3 |
+
size 743017
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