knowledge: upload immutable shard group
Browse files- knowledge/graph-e1-raw-fp16-v2/receipts/000392.json +1 -0
- knowledge/graph-e1-raw-fp16-v2/receipts/000393.json +1 -0
- knowledge/graph-e1-raw-fp16-v2/receipts/000394.json +1 -0
- knowledge/graph-e1-raw-fp16-v2/receipts/000395.json +1 -0
- knowledge/graph-e1-raw-fp16-v2/receipts/000396.json +1 -0
- knowledge/graph-e1-raw-fp16-v2/receipts/000397.json +1 -0
- knowledge/graph-e1-raw-fp16-v2/receipts/000398.json +1 -0
- knowledge/graph-e1-raw-fp16-v2/receipts/000399.json +1 -0
- knowledge/graph-e1-raw-fp16-v2/shards/000392.bin +3 -0
- knowledge/graph-e1-raw-fp16-v2/shards/000393.bin +3 -0
- knowledge/graph-e1-raw-fp16-v2/shards/000394.bin +3 -0
- knowledge/graph-e1-raw-fp16-v2/shards/000395.bin +3 -0
- knowledge/graph-e1-raw-fp16-v2/shards/000396.bin +3 -0
- knowledge/graph-e1-raw-fp16-v2/shards/000397.bin +3 -0
- knowledge/graph-e1-raw-fp16-v2/shards/000398.bin +3 -0
- knowledge/graph-e1-raw-fp16-v2/shards/000399.bin +3 -0
knowledge/graph-e1-raw-fp16-v2/receipts/000392.json
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
{"alignment_sha256":"7ab002083a85d80f41edd8413fe9a4295e9eb4a2229839c20a4ac7d144dbca57","artifact_path":"knowledge/graph-e1-raw-fp16-v2/shards/000392.bin","bytes":252238054,"fp16_bitwise_roundtrip":true,"fp16_payload_sha256":"7ef555b2aadf22f73f30fc0fb5ada56109786c76aaee31ea1c6a2a924a90467c","identity":{"actual_teacher_hf_revision":"9ce79652c1590997c8a3c84c420721774c90e363","cache_identity":"563bac05358fb4cb449e2b125d62a250dabded66e1cbe972801626c79359464a","checkpoint_path":"checkpoints/gch-e419-full-seed42-20261023-r1/checkpoint_step_359851.pt","checkpoint_sha256":"bded20ccb9fe69496ec55ebe3f630cef3d811c610353cf94944d322249a18a05","config_fingerprint":"a53fc42d105997e949fabf74a98f5ddb69a706da590803abbc07fb3eb349793b","dataset_fingerprint":"ccb6c5b7f1bddec623cd94a9fc146a4d268f35eaab666459de6b911732d4a32b","dataset_revision":"a1adc9749e294ccff4eaac376de1c78ef0ea33ca","extraction_git_commit":"a1ab5d28bb49b91aa4aafd8758b1c6d6e0c2f3eb","extraction_plan_fingerprint":"b1baaaa70695701f9dbd63db323b42d174a87f527c07e21053fe0fbc2f4d4fab","graph_enabled":true,"implementation_sha256":{"knowledge_batch_benchmark.py":"d1820d06951789fb4f891a87c51cf2467f6b66942dac59a4b6f12621adedecf0","knowledge_batching.py":"79fad817fb34fd2a65f1934c96bbc46ed856cd3333d112bcedd970bd9eb2b51f","knowledge_cpu_benchmark.py":"7799132ca843857aa574fb2ec98a906b9181c6080de377c37fc6fbaff6bad7ae","knowledge_cpu_profile.py":"b38dee1918bfcf3fcc37aefd1fd3077a294d19b3994212c91778b1acb27d3cd6","knowledge_engineering_benchmark.py":"ca255b151a75fc5df6be9565c5834be662f7bdf03dfea4bb812fdcad750b362b","knowledge_extraction.py":"b93fd25bdcdda7590c67f6a91e5cd0919b26d1b40decd52c3c4e823aa9396c7a","knowledge_full_pipeline.py":"0aca81dbbd0581c193c18fece95e3c6e7337223d10bb226af2a33a93edd7ad7c","knowledge_group_publication.py":"4c6e68612e67dce7a233ef26c2e6680353c68ececbfe332add06a2db76080406","knowledge_inference.py":"a08d5816628c887d63c121f9c65d7a3cd2e826fe66a31cc206f9a2c61ca3741e","knowledge_monitor.py":"d5374952b8cedb0a52f4c5e04f490a108e9a48e1062e4fd22b14cd68aa7f3ebd","knowledge_network_benchmark.py":"1346b3b5c7f959b7faa7cada563f1953b2c036653f689c7e6c88e268f847884a","knowledge_pipeline.py":"a421283f5115e710a7a8eafaa0725a3b3a3d394086067afd85a77eeedf04decb","knowledge_prefetch.py":"2da9ba2f717128f4e8199f5fa58cdbea3004cd662f875c29e03aa647a803ea4d","knowledge_production.py":"198d46406f8dbd5c37c7d478bb6e381dbab0a17afa693af1df00105fb40dc2db","knowledge_production_publication.py":"c1be2b97a84f1dc2df74926504dc914bff8fdca547dfb04c3f35143ba6e73254","knowledge_publication.py":"94e206a5d82066c3bf24ee803eec681d09cbbaf58d9efa879632ea96fc638f4e","knowledge_retry.py":"90d7da0c4e41e9a52904a8dafce462bc394218da276b72d1b8306cd480d6e3b6","knowledge_runtime_bundle.py":"9119c0dd7c1113211caac100ed4d263a6cd189ca589cc44d8c2d33fc43a6310d","knowledge_shard.py":"353c615df196f7ae6e68fba10b4a0d780c960c26dbc97a87469f004969ed2716","knowledge_source_prefetch.py":"662e5ebd2c0f18261eb24926c71128bef47cf5c04907d42a6e1c96b4775ace7a","knowledge_staging.py":"04476f37b5283fb806a07fa33b323848110fd5e8d128b29601fc910607497cff","knowledge_storage.py":"75569fb81878f3a30d0695e370b7d0085372cb461ea57f08e05651a608e59f7c","knowledge_stream_benchmark.py":"58813bbab04756c9608e2fabbc6035a62320170675246dc321b8369c4099e087","knowledge_teacher.py":"a1a7c2a5f9d98dba272253629a6b8880509cbcc70f05768e0b16b8f5c9cb8f43","knowledge_transport.py":"8abe7a81aa627a73cfead513834f415ab686a85073ef894f92faca8059fb2c61"},"limitations":["Parent producer/provenance/license-scope evidence remains unverified under issues 161 and 171.","Cross-split, near-duplicate and benchmark leakage checks remain unverified.","Published source/build plan is incomplete; full payload checksums have not been independently reproduced.","Author-reported payload observations are not independently reproduced research acceptance."],"metadata_sha256":{"resolved_config.json":"66b5da6f3336597d52bb8ab2b819941040f1b84d44344a06801bf0a1ae477f78","run.json":"ce1e369cf3dd6dc204aec8c9ab98c8bda1121291683f059bf5b12c8112da90f0","streaming_identity.json":"eff0460e7b26ccea0bce87e21cc26d04627fea883c3aeaf03d22550c701502a7"},"pipeline_version":2,"production_contract":{"batch_size":1024,"group_size":8,"layout":"packed_zstd1","queue_depth":8,"shard_rows":131072,"source_prefetch_depth":2},"runtime":{"cuda":"13.0","gpu":"NVIDIA RTX PRO 6000 Blackwell Server Edition","numpy":"2.2.6","precision":"bf16","pyarrow":"21.0.0","python":"3.13.11","recurrent_precision":"fp32","torch":"2.11.0+cu130"},"schema":{"channel_order":["form:0:5","tone:0:6","boundary:0:1","case:0:2"],"channels":14,"dtype":"<f2","logits":"final_post_graph_raw","padding_policy":"source_mask_true_only","schema_version":"graph_e1_raw_fp16_v1","split":"train","task_variant":"T2_JOINT","unsupported_policy":"retain_row_empty_logits"},"sealed_test_accessed":false,"source_manifest_sha256":"be0b123332b94fdad66f4c8bc9eb7c9fed93596b053d83e43581fb04398a3492","source_train_files_sha256":"eb3c1b65b844e1081a3ecf79065c12d6bc2b6a341b01dbfdacf120e4fbe6f279","strict_state_restore":true,"teacher_git_commit":"ae0250338a1ce4ea51c980f523a7e084ff668510","teacher_parameter_count":4236728,"teacher_run_id":"gch-e419-full-seed42-20261023-r1"},"layout":"packed_zstd1","raw_count":131072,"row_end":51511296,"row_start":51380224,"sha256":"7d970ea3ae92294c9b136a224edd202e135a3cdbcf3dedd56854e3161214c733","shard":392,"state":"UPLOADED","supported_count":130925,"token_count":11654840,"unsupported_count":147}
|
knowledge/graph-e1-raw-fp16-v2/receipts/000393.json
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
{"alignment_sha256":"ff6f258a9b3ccbc97b684e77b07c9be3eebb63d96142da96053f4384ec1fe152","artifact_path":"knowledge/graph-e1-raw-fp16-v2/shards/000393.bin","bytes":251365322,"fp16_bitwise_roundtrip":true,"fp16_payload_sha256":"d86333cc6d42ef8728774979a86e954cfa3d8562e0cd7b4e5f927b0489c6ba8f","identity":{"actual_teacher_hf_revision":"9ce79652c1590997c8a3c84c420721774c90e363","cache_identity":"563bac05358fb4cb449e2b125d62a250dabded66e1cbe972801626c79359464a","checkpoint_path":"checkpoints/gch-e419-full-seed42-20261023-r1/checkpoint_step_359851.pt","checkpoint_sha256":"bded20ccb9fe69496ec55ebe3f630cef3d811c610353cf94944d322249a18a05","config_fingerprint":"a53fc42d105997e949fabf74a98f5ddb69a706da590803abbc07fb3eb349793b","dataset_fingerprint":"ccb6c5b7f1bddec623cd94a9fc146a4d268f35eaab666459de6b911732d4a32b","dataset_revision":"a1adc9749e294ccff4eaac376de1c78ef0ea33ca","extraction_git_commit":"a1ab5d28bb49b91aa4aafd8758b1c6d6e0c2f3eb","extraction_plan_fingerprint":"b1baaaa70695701f9dbd63db323b42d174a87f527c07e21053fe0fbc2f4d4fab","graph_enabled":true,"implementation_sha256":{"knowledge_batch_benchmark.py":"d1820d06951789fb4f891a87c51cf2467f6b66942dac59a4b6f12621adedecf0","knowledge_batching.py":"79fad817fb34fd2a65f1934c96bbc46ed856cd3333d112bcedd970bd9eb2b51f","knowledge_cpu_benchmark.py":"7799132ca843857aa574fb2ec98a906b9181c6080de377c37fc6fbaff6bad7ae","knowledge_cpu_profile.py":"b38dee1918bfcf3fcc37aefd1fd3077a294d19b3994212c91778b1acb27d3cd6","knowledge_engineering_benchmark.py":"ca255b151a75fc5df6be9565c5834be662f7bdf03dfea4bb812fdcad750b362b","knowledge_extraction.py":"b93fd25bdcdda7590c67f6a91e5cd0919b26d1b40decd52c3c4e823aa9396c7a","knowledge_full_pipeline.py":"0aca81dbbd0581c193c18fece95e3c6e7337223d10bb226af2a33a93edd7ad7c","knowledge_group_publication.py":"4c6e68612e67dce7a233ef26c2e6680353c68ececbfe332add06a2db76080406","knowledge_inference.py":"a08d5816628c887d63c121f9c65d7a3cd2e826fe66a31cc206f9a2c61ca3741e","knowledge_monitor.py":"d5374952b8cedb0a52f4c5e04f490a108e9a48e1062e4fd22b14cd68aa7f3ebd","knowledge_network_benchmark.py":"1346b3b5c7f959b7faa7cada563f1953b2c036653f689c7e6c88e268f847884a","knowledge_pipeline.py":"a421283f5115e710a7a8eafaa0725a3b3a3d394086067afd85a77eeedf04decb","knowledge_prefetch.py":"2da9ba2f717128f4e8199f5fa58cdbea3004cd662f875c29e03aa647a803ea4d","knowledge_production.py":"198d46406f8dbd5c37c7d478bb6e381dbab0a17afa693af1df00105fb40dc2db","knowledge_production_publication.py":"c1be2b97a84f1dc2df74926504dc914bff8fdca547dfb04c3f35143ba6e73254","knowledge_publication.py":"94e206a5d82066c3bf24ee803eec681d09cbbaf58d9efa879632ea96fc638f4e","knowledge_retry.py":"90d7da0c4e41e9a52904a8dafce462bc394218da276b72d1b8306cd480d6e3b6","knowledge_runtime_bundle.py":"9119c0dd7c1113211caac100ed4d263a6cd189ca589cc44d8c2d33fc43a6310d","knowledge_shard.py":"353c615df196f7ae6e68fba10b4a0d780c960c26dbc97a87469f004969ed2716","knowledge_source_prefetch.py":"662e5ebd2c0f18261eb24926c71128bef47cf5c04907d42a6e1c96b4775ace7a","knowledge_staging.py":"04476f37b5283fb806a07fa33b323848110fd5e8d128b29601fc910607497cff","knowledge_storage.py":"75569fb81878f3a30d0695e370b7d0085372cb461ea57f08e05651a608e59f7c","knowledge_stream_benchmark.py":"58813bbab04756c9608e2fabbc6035a62320170675246dc321b8369c4099e087","knowledge_teacher.py":"a1a7c2a5f9d98dba272253629a6b8880509cbcc70f05768e0b16b8f5c9cb8f43","knowledge_transport.py":"8abe7a81aa627a73cfead513834f415ab686a85073ef894f92faca8059fb2c61"},"limitations":["Parent producer/provenance/license-scope evidence remains unverified under issues 161 and 171.","Cross-split, near-duplicate and benchmark leakage checks remain unverified.","Published source/build plan is incomplete; full payload checksums have not been independently reproduced.","Author-reported payload observations are not independently reproduced research acceptance."],"metadata_sha256":{"resolved_config.json":"66b5da6f3336597d52bb8ab2b819941040f1b84d44344a06801bf0a1ae477f78","run.json":"ce1e369cf3dd6dc204aec8c9ab98c8bda1121291683f059bf5b12c8112da90f0","streaming_identity.json":"eff0460e7b26ccea0bce87e21cc26d04627fea883c3aeaf03d22550c701502a7"},"pipeline_version":2,"production_contract":{"batch_size":1024,"group_size":8,"layout":"packed_zstd1","queue_depth":8,"shard_rows":131072,"source_prefetch_depth":2},"runtime":{"cuda":"13.0","gpu":"NVIDIA RTX PRO 6000 Blackwell Server Edition","numpy":"2.2.6","precision":"bf16","pyarrow":"21.0.0","python":"3.13.11","recurrent_precision":"fp32","torch":"2.11.0+cu130"},"schema":{"channel_order":["form:0:5","tone:0:6","boundary:0:1","case:0:2"],"channels":14,"dtype":"<f2","logits":"final_post_graph_raw","padding_policy":"source_mask_true_only","schema_version":"graph_e1_raw_fp16_v1","split":"train","task_variant":"T2_JOINT","unsupported_policy":"retain_row_empty_logits"},"sealed_test_accessed":false,"source_manifest_sha256":"be0b123332b94fdad66f4c8bc9eb7c9fed93596b053d83e43581fb04398a3492","source_train_files_sha256":"eb3c1b65b844e1081a3ecf79065c12d6bc2b6a341b01dbfdacf120e4fbe6f279","strict_state_restore":true,"teacher_git_commit":"ae0250338a1ce4ea51c980f523a7e084ff668510","teacher_parameter_count":4236728,"teacher_run_id":"gch-e419-full-seed42-20261023-r1"},"layout":"packed_zstd1","raw_count":131072,"row_end":51642368,"row_start":51511296,"sha256":"a04ef4ffa35aac37acf6ef035d907622a256f7eb193b76fa6d0538322ceffa49","shard":393,"state":"UPLOADED","supported_count":130925,"token_count":11613924,"unsupported_count":147}
|
knowledge/graph-e1-raw-fp16-v2/receipts/000394.json
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
{"alignment_sha256":"74831fe3d4eac9f1c6af64c6ed87c271bdff373d90ce0ca266e937d104bbbd82","artifact_path":"knowledge/graph-e1-raw-fp16-v2/shards/000394.bin","bytes":251399524,"fp16_bitwise_roundtrip":true,"fp16_payload_sha256":"0bffa9152c2991017ada74c7374fd500f4132948558252d7c42e1b021069f659","identity":{"actual_teacher_hf_revision":"9ce79652c1590997c8a3c84c420721774c90e363","cache_identity":"563bac05358fb4cb449e2b125d62a250dabded66e1cbe972801626c79359464a","checkpoint_path":"checkpoints/gch-e419-full-seed42-20261023-r1/checkpoint_step_359851.pt","checkpoint_sha256":"bded20ccb9fe69496ec55ebe3f630cef3d811c610353cf94944d322249a18a05","config_fingerprint":"a53fc42d105997e949fabf74a98f5ddb69a706da590803abbc07fb3eb349793b","dataset_fingerprint":"ccb6c5b7f1bddec623cd94a9fc146a4d268f35eaab666459de6b911732d4a32b","dataset_revision":"a1adc9749e294ccff4eaac376de1c78ef0ea33ca","extraction_git_commit":"a1ab5d28bb49b91aa4aafd8758b1c6d6e0c2f3eb","extraction_plan_fingerprint":"b1baaaa70695701f9dbd63db323b42d174a87f527c07e21053fe0fbc2f4d4fab","graph_enabled":true,"implementation_sha256":{"knowledge_batch_benchmark.py":"d1820d06951789fb4f891a87c51cf2467f6b66942dac59a4b6f12621adedecf0","knowledge_batching.py":"79fad817fb34fd2a65f1934c96bbc46ed856cd3333d112bcedd970bd9eb2b51f","knowledge_cpu_benchmark.py":"7799132ca843857aa574fb2ec98a906b9181c6080de377c37fc6fbaff6bad7ae","knowledge_cpu_profile.py":"b38dee1918bfcf3fcc37aefd1fd3077a294d19b3994212c91778b1acb27d3cd6","knowledge_engineering_benchmark.py":"ca255b151a75fc5df6be9565c5834be662f7bdf03dfea4bb812fdcad750b362b","knowledge_extraction.py":"b93fd25bdcdda7590c67f6a91e5cd0919b26d1b40decd52c3c4e823aa9396c7a","knowledge_full_pipeline.py":"0aca81dbbd0581c193c18fece95e3c6e7337223d10bb226af2a33a93edd7ad7c","knowledge_group_publication.py":"4c6e68612e67dce7a233ef26c2e6680353c68ececbfe332add06a2db76080406","knowledge_inference.py":"a08d5816628c887d63c121f9c65d7a3cd2e826fe66a31cc206f9a2c61ca3741e","knowledge_monitor.py":"d5374952b8cedb0a52f4c5e04f490a108e9a48e1062e4fd22b14cd68aa7f3ebd","knowledge_network_benchmark.py":"1346b3b5c7f959b7faa7cada563f1953b2c036653f689c7e6c88e268f847884a","knowledge_pipeline.py":"a421283f5115e710a7a8eafaa0725a3b3a3d394086067afd85a77eeedf04decb","knowledge_prefetch.py":"2da9ba2f717128f4e8199f5fa58cdbea3004cd662f875c29e03aa647a803ea4d","knowledge_production.py":"198d46406f8dbd5c37c7d478bb6e381dbab0a17afa693af1df00105fb40dc2db","knowledge_production_publication.py":"c1be2b97a84f1dc2df74926504dc914bff8fdca547dfb04c3f35143ba6e73254","knowledge_publication.py":"94e206a5d82066c3bf24ee803eec681d09cbbaf58d9efa879632ea96fc638f4e","knowledge_retry.py":"90d7da0c4e41e9a52904a8dafce462bc394218da276b72d1b8306cd480d6e3b6","knowledge_runtime_bundle.py":"9119c0dd7c1113211caac100ed4d263a6cd189ca589cc44d8c2d33fc43a6310d","knowledge_shard.py":"353c615df196f7ae6e68fba10b4a0d780c960c26dbc97a87469f004969ed2716","knowledge_source_prefetch.py":"662e5ebd2c0f18261eb24926c71128bef47cf5c04907d42a6e1c96b4775ace7a","knowledge_staging.py":"04476f37b5283fb806a07fa33b323848110fd5e8d128b29601fc910607497cff","knowledge_storage.py":"75569fb81878f3a30d0695e370b7d0085372cb461ea57f08e05651a608e59f7c","knowledge_stream_benchmark.py":"58813bbab04756c9608e2fabbc6035a62320170675246dc321b8369c4099e087","knowledge_teacher.py":"a1a7c2a5f9d98dba272253629a6b8880509cbcc70f05768e0b16b8f5c9cb8f43","knowledge_transport.py":"8abe7a81aa627a73cfead513834f415ab686a85073ef894f92faca8059fb2c61"},"limitations":["Parent producer/provenance/license-scope evidence remains unverified under issues 161 and 171.","Cross-split, near-duplicate and benchmark leakage checks remain unverified.","Published source/build plan is incomplete; full payload checksums have not been independently reproduced.","Author-reported payload observations are not independently reproduced research acceptance."],"metadata_sha256":{"resolved_config.json":"66b5da6f3336597d52bb8ab2b819941040f1b84d44344a06801bf0a1ae477f78","run.json":"ce1e369cf3dd6dc204aec8c9ab98c8bda1121291683f059bf5b12c8112da90f0","streaming_identity.json":"eff0460e7b26ccea0bce87e21cc26d04627fea883c3aeaf03d22550c701502a7"},"pipeline_version":2,"production_contract":{"batch_size":1024,"group_size":8,"layout":"packed_zstd1","queue_depth":8,"shard_rows":131072,"source_prefetch_depth":2},"runtime":{"cuda":"13.0","gpu":"NVIDIA RTX PRO 6000 Blackwell Server Edition","numpy":"2.2.6","precision":"bf16","pyarrow":"21.0.0","python":"3.13.11","recurrent_precision":"fp32","torch":"2.11.0+cu130"},"schema":{"channel_order":["form:0:5","tone:0:6","boundary:0:1","case:0:2"],"channels":14,"dtype":"<f2","logits":"final_post_graph_raw","padding_policy":"source_mask_true_only","schema_version":"graph_e1_raw_fp16_v1","split":"train","task_variant":"T2_JOINT","unsupported_policy":"retain_row_empty_logits"},"sealed_test_accessed":false,"source_manifest_sha256":"be0b123332b94fdad66f4c8bc9eb7c9fed93596b053d83e43581fb04398a3492","source_train_files_sha256":"eb3c1b65b844e1081a3ecf79065c12d6bc2b6a341b01dbfdacf120e4fbe6f279","strict_state_restore":true,"teacher_git_commit":"ae0250338a1ce4ea51c980f523a7e084ff668510","teacher_parameter_count":4236728,"teacher_run_id":"gch-e419-full-seed42-20261023-r1"},"layout":"packed_zstd1","raw_count":131072,"row_end":51773440,"row_start":51642368,"sha256":"a4df05071997ecf3a07d5372a866b28c2efc42f965e0aeaa7886eab07801e355","shard":394,"state":"UPLOADED","supported_count":130924,"token_count":11615415,"unsupported_count":148}
|
knowledge/graph-e1-raw-fp16-v2/receipts/000395.json
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
{"alignment_sha256":"7dbf9e76f4c0ded99629f866f5e010253b3a283051f5cadab839280dc2ce8a32","artifact_path":"knowledge/graph-e1-raw-fp16-v2/shards/000395.bin","bytes":252014210,"fp16_bitwise_roundtrip":true,"fp16_payload_sha256":"b295c880236603b7b5533fe17b2c9e478cce6891a7542d8821c29d2228ccf18f","identity":{"actual_teacher_hf_revision":"9ce79652c1590997c8a3c84c420721774c90e363","cache_identity":"563bac05358fb4cb449e2b125d62a250dabded66e1cbe972801626c79359464a","checkpoint_path":"checkpoints/gch-e419-full-seed42-20261023-r1/checkpoint_step_359851.pt","checkpoint_sha256":"bded20ccb9fe69496ec55ebe3f630cef3d811c610353cf94944d322249a18a05","config_fingerprint":"a53fc42d105997e949fabf74a98f5ddb69a706da590803abbc07fb3eb349793b","dataset_fingerprint":"ccb6c5b7f1bddec623cd94a9fc146a4d268f35eaab666459de6b911732d4a32b","dataset_revision":"a1adc9749e294ccff4eaac376de1c78ef0ea33ca","extraction_git_commit":"a1ab5d28bb49b91aa4aafd8758b1c6d6e0c2f3eb","extraction_plan_fingerprint":"b1baaaa70695701f9dbd63db323b42d174a87f527c07e21053fe0fbc2f4d4fab","graph_enabled":true,"implementation_sha256":{"knowledge_batch_benchmark.py":"d1820d06951789fb4f891a87c51cf2467f6b66942dac59a4b6f12621adedecf0","knowledge_batching.py":"79fad817fb34fd2a65f1934c96bbc46ed856cd3333d112bcedd970bd9eb2b51f","knowledge_cpu_benchmark.py":"7799132ca843857aa574fb2ec98a906b9181c6080de377c37fc6fbaff6bad7ae","knowledge_cpu_profile.py":"b38dee1918bfcf3fcc37aefd1fd3077a294d19b3994212c91778b1acb27d3cd6","knowledge_engineering_benchmark.py":"ca255b151a75fc5df6be9565c5834be662f7bdf03dfea4bb812fdcad750b362b","knowledge_extraction.py":"b93fd25bdcdda7590c67f6a91e5cd0919b26d1b40decd52c3c4e823aa9396c7a","knowledge_full_pipeline.py":"0aca81dbbd0581c193c18fece95e3c6e7337223d10bb226af2a33a93edd7ad7c","knowledge_group_publication.py":"4c6e68612e67dce7a233ef26c2e6680353c68ececbfe332add06a2db76080406","knowledge_inference.py":"a08d5816628c887d63c121f9c65d7a3cd2e826fe66a31cc206f9a2c61ca3741e","knowledge_monitor.py":"d5374952b8cedb0a52f4c5e04f490a108e9a48e1062e4fd22b14cd68aa7f3ebd","knowledge_network_benchmark.py":"1346b3b5c7f959b7faa7cada563f1953b2c036653f689c7e6c88e268f847884a","knowledge_pipeline.py":"a421283f5115e710a7a8eafaa0725a3b3a3d394086067afd85a77eeedf04decb","knowledge_prefetch.py":"2da9ba2f717128f4e8199f5fa58cdbea3004cd662f875c29e03aa647a803ea4d","knowledge_production.py":"198d46406f8dbd5c37c7d478bb6e381dbab0a17afa693af1df00105fb40dc2db","knowledge_production_publication.py":"c1be2b97a84f1dc2df74926504dc914bff8fdca547dfb04c3f35143ba6e73254","knowledge_publication.py":"94e206a5d82066c3bf24ee803eec681d09cbbaf58d9efa879632ea96fc638f4e","knowledge_retry.py":"90d7da0c4e41e9a52904a8dafce462bc394218da276b72d1b8306cd480d6e3b6","knowledge_runtime_bundle.py":"9119c0dd7c1113211caac100ed4d263a6cd189ca589cc44d8c2d33fc43a6310d","knowledge_shard.py":"353c615df196f7ae6e68fba10b4a0d780c960c26dbc97a87469f004969ed2716","knowledge_source_prefetch.py":"662e5ebd2c0f18261eb24926c71128bef47cf5c04907d42a6e1c96b4775ace7a","knowledge_staging.py":"04476f37b5283fb806a07fa33b323848110fd5e8d128b29601fc910607497cff","knowledge_storage.py":"75569fb81878f3a30d0695e370b7d0085372cb461ea57f08e05651a608e59f7c","knowledge_stream_benchmark.py":"58813bbab04756c9608e2fabbc6035a62320170675246dc321b8369c4099e087","knowledge_teacher.py":"a1a7c2a5f9d98dba272253629a6b8880509cbcc70f05768e0b16b8f5c9cb8f43","knowledge_transport.py":"8abe7a81aa627a73cfead513834f415ab686a85073ef894f92faca8059fb2c61"},"limitations":["Parent producer/provenance/license-scope evidence remains unverified under issues 161 and 171.","Cross-split, near-duplicate and benchmark leakage checks remain unverified.","Published source/build plan is incomplete; full payload checksums have not been independently reproduced.","Author-reported payload observations are not independently reproduced research acceptance."],"metadata_sha256":{"resolved_config.json":"66b5da6f3336597d52bb8ab2b819941040f1b84d44344a06801bf0a1ae477f78","run.json":"ce1e369cf3dd6dc204aec8c9ab98c8bda1121291683f059bf5b12c8112da90f0","streaming_identity.json":"eff0460e7b26ccea0bce87e21cc26d04627fea883c3aeaf03d22550c701502a7"},"pipeline_version":2,"production_contract":{"batch_size":1024,"group_size":8,"layout":"packed_zstd1","queue_depth":8,"shard_rows":131072,"source_prefetch_depth":2},"runtime":{"cuda":"13.0","gpu":"NVIDIA RTX PRO 6000 Blackwell Server Edition","numpy":"2.2.6","precision":"bf16","pyarrow":"21.0.0","python":"3.13.11","recurrent_precision":"fp32","torch":"2.11.0+cu130"},"schema":{"channel_order":["form:0:5","tone:0:6","boundary:0:1","case:0:2"],"channels":14,"dtype":"<f2","logits":"final_post_graph_raw","padding_policy":"source_mask_true_only","schema_version":"graph_e1_raw_fp16_v1","split":"train","task_variant":"T2_JOINT","unsupported_policy":"retain_row_empty_logits"},"sealed_test_accessed":false,"source_manifest_sha256":"be0b123332b94fdad66f4c8bc9eb7c9fed93596b053d83e43581fb04398a3492","source_train_files_sha256":"eb3c1b65b844e1081a3ecf79065c12d6bc2b6a341b01dbfdacf120e4fbe6f279","strict_state_restore":true,"teacher_git_commit":"ae0250338a1ce4ea51c980f523a7e084ff668510","teacher_parameter_count":4236728,"teacher_run_id":"gch-e419-full-seed42-20261023-r1"},"layout":"packed_zstd1","raw_count":131072,"row_end":51904512,"row_start":51773440,"sha256":"be8b7b45ce5f7246a42d173db7ea218f3775ac013ca5c3570ec8e4908fedc1ed","shard":395,"state":"UPLOADED","supported_count":130903,"token_count":11644459,"unsupported_count":169}
|
knowledge/graph-e1-raw-fp16-v2/receipts/000396.json
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
{"alignment_sha256":"f496cd2c059b0db19612023b203d2422361d5ee7b07a341227cde9efcb306ea4","artifact_path":"knowledge/graph-e1-raw-fp16-v2/shards/000396.bin","bytes":252187763,"fp16_bitwise_roundtrip":true,"fp16_payload_sha256":"82af92301a9c5424718f9fd523c182d74b328b87138109f4d186a2db5ebde5ac","identity":{"actual_teacher_hf_revision":"9ce79652c1590997c8a3c84c420721774c90e363","cache_identity":"563bac05358fb4cb449e2b125d62a250dabded66e1cbe972801626c79359464a","checkpoint_path":"checkpoints/gch-e419-full-seed42-20261023-r1/checkpoint_step_359851.pt","checkpoint_sha256":"bded20ccb9fe69496ec55ebe3f630cef3d811c610353cf94944d322249a18a05","config_fingerprint":"a53fc42d105997e949fabf74a98f5ddb69a706da590803abbc07fb3eb349793b","dataset_fingerprint":"ccb6c5b7f1bddec623cd94a9fc146a4d268f35eaab666459de6b911732d4a32b","dataset_revision":"a1adc9749e294ccff4eaac376de1c78ef0ea33ca","extraction_git_commit":"a1ab5d28bb49b91aa4aafd8758b1c6d6e0c2f3eb","extraction_plan_fingerprint":"b1baaaa70695701f9dbd63db323b42d174a87f527c07e21053fe0fbc2f4d4fab","graph_enabled":true,"implementation_sha256":{"knowledge_batch_benchmark.py":"d1820d06951789fb4f891a87c51cf2467f6b66942dac59a4b6f12621adedecf0","knowledge_batching.py":"79fad817fb34fd2a65f1934c96bbc46ed856cd3333d112bcedd970bd9eb2b51f","knowledge_cpu_benchmark.py":"7799132ca843857aa574fb2ec98a906b9181c6080de377c37fc6fbaff6bad7ae","knowledge_cpu_profile.py":"b38dee1918bfcf3fcc37aefd1fd3077a294d19b3994212c91778b1acb27d3cd6","knowledge_engineering_benchmark.py":"ca255b151a75fc5df6be9565c5834be662f7bdf03dfea4bb812fdcad750b362b","knowledge_extraction.py":"b93fd25bdcdda7590c67f6a91e5cd0919b26d1b40decd52c3c4e823aa9396c7a","knowledge_full_pipeline.py":"0aca81dbbd0581c193c18fece95e3c6e7337223d10bb226af2a33a93edd7ad7c","knowledge_group_publication.py":"4c6e68612e67dce7a233ef26c2e6680353c68ececbfe332add06a2db76080406","knowledge_inference.py":"a08d5816628c887d63c121f9c65d7a3cd2e826fe66a31cc206f9a2c61ca3741e","knowledge_monitor.py":"d5374952b8cedb0a52f4c5e04f490a108e9a48e1062e4fd22b14cd68aa7f3ebd","knowledge_network_benchmark.py":"1346b3b5c7f959b7faa7cada563f1953b2c036653f689c7e6c88e268f847884a","knowledge_pipeline.py":"a421283f5115e710a7a8eafaa0725a3b3a3d394086067afd85a77eeedf04decb","knowledge_prefetch.py":"2da9ba2f717128f4e8199f5fa58cdbea3004cd662f875c29e03aa647a803ea4d","knowledge_production.py":"198d46406f8dbd5c37c7d478bb6e381dbab0a17afa693af1df00105fb40dc2db","knowledge_production_publication.py":"c1be2b97a84f1dc2df74926504dc914bff8fdca547dfb04c3f35143ba6e73254","knowledge_publication.py":"94e206a5d82066c3bf24ee803eec681d09cbbaf58d9efa879632ea96fc638f4e","knowledge_retry.py":"90d7da0c4e41e9a52904a8dafce462bc394218da276b72d1b8306cd480d6e3b6","knowledge_runtime_bundle.py":"9119c0dd7c1113211caac100ed4d263a6cd189ca589cc44d8c2d33fc43a6310d","knowledge_shard.py":"353c615df196f7ae6e68fba10b4a0d780c960c26dbc97a87469f004969ed2716","knowledge_source_prefetch.py":"662e5ebd2c0f18261eb24926c71128bef47cf5c04907d42a6e1c96b4775ace7a","knowledge_staging.py":"04476f37b5283fb806a07fa33b323848110fd5e8d128b29601fc910607497cff","knowledge_storage.py":"75569fb81878f3a30d0695e370b7d0085372cb461ea57f08e05651a608e59f7c","knowledge_stream_benchmark.py":"58813bbab04756c9608e2fabbc6035a62320170675246dc321b8369c4099e087","knowledge_teacher.py":"a1a7c2a5f9d98dba272253629a6b8880509cbcc70f05768e0b16b8f5c9cb8f43","knowledge_transport.py":"8abe7a81aa627a73cfead513834f415ab686a85073ef894f92faca8059fb2c61"},"limitations":["Parent producer/provenance/license-scope evidence remains unverified under issues 161 and 171.","Cross-split, near-duplicate and benchmark leakage checks remain unverified.","Published source/build plan is incomplete; full payload checksums have not been independently reproduced.","Author-reported payload observations are not independently reproduced research acceptance."],"metadata_sha256":{"resolved_config.json":"66b5da6f3336597d52bb8ab2b819941040f1b84d44344a06801bf0a1ae477f78","run.json":"ce1e369cf3dd6dc204aec8c9ab98c8bda1121291683f059bf5b12c8112da90f0","streaming_identity.json":"eff0460e7b26ccea0bce87e21cc26d04627fea883c3aeaf03d22550c701502a7"},"pipeline_version":2,"production_contract":{"batch_size":1024,"group_size":8,"layout":"packed_zstd1","queue_depth":8,"shard_rows":131072,"source_prefetch_depth":2},"runtime":{"cuda":"13.0","gpu":"NVIDIA RTX PRO 6000 Blackwell Server Edition","numpy":"2.2.6","precision":"bf16","pyarrow":"21.0.0","python":"3.13.11","recurrent_precision":"fp32","torch":"2.11.0+cu130"},"schema":{"channel_order":["form:0:5","tone:0:6","boundary:0:1","case:0:2"],"channels":14,"dtype":"<f2","logits":"final_post_graph_raw","padding_policy":"source_mask_true_only","schema_version":"graph_e1_raw_fp16_v1","split":"train","task_variant":"T2_JOINT","unsupported_policy":"retain_row_empty_logits"},"sealed_test_accessed":false,"source_manifest_sha256":"be0b123332b94fdad66f4c8bc9eb7c9fed93596b053d83e43581fb04398a3492","source_train_files_sha256":"eb3c1b65b844e1081a3ecf79065c12d6bc2b6a341b01dbfdacf120e4fbe6f279","strict_state_restore":true,"teacher_git_commit":"ae0250338a1ce4ea51c980f523a7e084ff668510","teacher_parameter_count":4236728,"teacher_run_id":"gch-e419-full-seed42-20261023-r1"},"layout":"packed_zstd1","raw_count":131072,"row_end":52035584,"row_start":51904512,"sha256":"6b03d189f32fc0cbddcf5dc439422c013dd378ce56ba886122d4ff6eddd9f3de","shard":396,"state":"UPLOADED","supported_count":130912,"token_count":11652327,"unsupported_count":160}
|
knowledge/graph-e1-raw-fp16-v2/receipts/000397.json
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
{"alignment_sha256":"096d4c34b4f74a5a649ea3ea81a3e189f4094190aa705f5930df3f611a372cb2","artifact_path":"knowledge/graph-e1-raw-fp16-v2/shards/000397.bin","bytes":251995107,"fp16_bitwise_roundtrip":true,"fp16_payload_sha256":"532f103383265851de11450f3706e3e01f8cdbba617291373ad745119e8a5642","identity":{"actual_teacher_hf_revision":"9ce79652c1590997c8a3c84c420721774c90e363","cache_identity":"563bac05358fb4cb449e2b125d62a250dabded66e1cbe972801626c79359464a","checkpoint_path":"checkpoints/gch-e419-full-seed42-20261023-r1/checkpoint_step_359851.pt","checkpoint_sha256":"bded20ccb9fe69496ec55ebe3f630cef3d811c610353cf94944d322249a18a05","config_fingerprint":"a53fc42d105997e949fabf74a98f5ddb69a706da590803abbc07fb3eb349793b","dataset_fingerprint":"ccb6c5b7f1bddec623cd94a9fc146a4d268f35eaab666459de6b911732d4a32b","dataset_revision":"a1adc9749e294ccff4eaac376de1c78ef0ea33ca","extraction_git_commit":"a1ab5d28bb49b91aa4aafd8758b1c6d6e0c2f3eb","extraction_plan_fingerprint":"b1baaaa70695701f9dbd63db323b42d174a87f527c07e21053fe0fbc2f4d4fab","graph_enabled":true,"implementation_sha256":{"knowledge_batch_benchmark.py":"d1820d06951789fb4f891a87c51cf2467f6b66942dac59a4b6f12621adedecf0","knowledge_batching.py":"79fad817fb34fd2a65f1934c96bbc46ed856cd3333d112bcedd970bd9eb2b51f","knowledge_cpu_benchmark.py":"7799132ca843857aa574fb2ec98a906b9181c6080de377c37fc6fbaff6bad7ae","knowledge_cpu_profile.py":"b38dee1918bfcf3fcc37aefd1fd3077a294d19b3994212c91778b1acb27d3cd6","knowledge_engineering_benchmark.py":"ca255b151a75fc5df6be9565c5834be662f7bdf03dfea4bb812fdcad750b362b","knowledge_extraction.py":"b93fd25bdcdda7590c67f6a91e5cd0919b26d1b40decd52c3c4e823aa9396c7a","knowledge_full_pipeline.py":"0aca81dbbd0581c193c18fece95e3c6e7337223d10bb226af2a33a93edd7ad7c","knowledge_group_publication.py":"4c6e68612e67dce7a233ef26c2e6680353c68ececbfe332add06a2db76080406","knowledge_inference.py":"a08d5816628c887d63c121f9c65d7a3cd2e826fe66a31cc206f9a2c61ca3741e","knowledge_monitor.py":"d5374952b8cedb0a52f4c5e04f490a108e9a48e1062e4fd22b14cd68aa7f3ebd","knowledge_network_benchmark.py":"1346b3b5c7f959b7faa7cada563f1953b2c036653f689c7e6c88e268f847884a","knowledge_pipeline.py":"a421283f5115e710a7a8eafaa0725a3b3a3d394086067afd85a77eeedf04decb","knowledge_prefetch.py":"2da9ba2f717128f4e8199f5fa58cdbea3004cd662f875c29e03aa647a803ea4d","knowledge_production.py":"198d46406f8dbd5c37c7d478bb6e381dbab0a17afa693af1df00105fb40dc2db","knowledge_production_publication.py":"c1be2b97a84f1dc2df74926504dc914bff8fdca547dfb04c3f35143ba6e73254","knowledge_publication.py":"94e206a5d82066c3bf24ee803eec681d09cbbaf58d9efa879632ea96fc638f4e","knowledge_retry.py":"90d7da0c4e41e9a52904a8dafce462bc394218da276b72d1b8306cd480d6e3b6","knowledge_runtime_bundle.py":"9119c0dd7c1113211caac100ed4d263a6cd189ca589cc44d8c2d33fc43a6310d","knowledge_shard.py":"353c615df196f7ae6e68fba10b4a0d780c960c26dbc97a87469f004969ed2716","knowledge_source_prefetch.py":"662e5ebd2c0f18261eb24926c71128bef47cf5c04907d42a6e1c96b4775ace7a","knowledge_staging.py":"04476f37b5283fb806a07fa33b323848110fd5e8d128b29601fc910607497cff","knowledge_storage.py":"75569fb81878f3a30d0695e370b7d0085372cb461ea57f08e05651a608e59f7c","knowledge_stream_benchmark.py":"58813bbab04756c9608e2fabbc6035a62320170675246dc321b8369c4099e087","knowledge_teacher.py":"a1a7c2a5f9d98dba272253629a6b8880509cbcc70f05768e0b16b8f5c9cb8f43","knowledge_transport.py":"8abe7a81aa627a73cfead513834f415ab686a85073ef894f92faca8059fb2c61"},"limitations":["Parent producer/provenance/license-scope evidence remains unverified under issues 161 and 171.","Cross-split, near-duplicate and benchmark leakage checks remain unverified.","Published source/build plan is incomplete; full payload checksums have not been independently reproduced.","Author-reported payload observations are not independently reproduced research acceptance."],"metadata_sha256":{"resolved_config.json":"66b5da6f3336597d52bb8ab2b819941040f1b84d44344a06801bf0a1ae477f78","run.json":"ce1e369cf3dd6dc204aec8c9ab98c8bda1121291683f059bf5b12c8112da90f0","streaming_identity.json":"eff0460e7b26ccea0bce87e21cc26d04627fea883c3aeaf03d22550c701502a7"},"pipeline_version":2,"production_contract":{"batch_size":1024,"group_size":8,"layout":"packed_zstd1","queue_depth":8,"shard_rows":131072,"source_prefetch_depth":2},"runtime":{"cuda":"13.0","gpu":"NVIDIA RTX PRO 6000 Blackwell Server Edition","numpy":"2.2.6","precision":"bf16","pyarrow":"21.0.0","python":"3.13.11","recurrent_precision":"fp32","torch":"2.11.0+cu130"},"schema":{"channel_order":["form:0:5","tone:0:6","boundary:0:1","case:0:2"],"channels":14,"dtype":"<f2","logits":"final_post_graph_raw","padding_policy":"source_mask_true_only","schema_version":"graph_e1_raw_fp16_v1","split":"train","task_variant":"T2_JOINT","unsupported_policy":"retain_row_empty_logits"},"sealed_test_accessed":false,"source_manifest_sha256":"be0b123332b94fdad66f4c8bc9eb7c9fed93596b053d83e43581fb04398a3492","source_train_files_sha256":"eb3c1b65b844e1081a3ecf79065c12d6bc2b6a341b01dbfdacf120e4fbe6f279","strict_state_restore":true,"teacher_git_commit":"ae0250338a1ce4ea51c980f523a7e084ff668510","teacher_parameter_count":4236728,"teacher_run_id":"gch-e419-full-seed42-20261023-r1"},"layout":"packed_zstd1","raw_count":131072,"row_end":52166656,"row_start":52035584,"sha256":"e95c2a778fac9a6a95a64df8b65eaf4fb2f71a6a66f8e44721cadde92d6da1ef","shard":397,"state":"UPLOADED","supported_count":130932,"token_count":11643774,"unsupported_count":140}
|
knowledge/graph-e1-raw-fp16-v2/receipts/000398.json
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
{"alignment_sha256":"fdfaeef4a35349c1190cf5d563c803f1f66327ff092334c2c4e13a7b2aabb867","artifact_path":"knowledge/graph-e1-raw-fp16-v2/shards/000398.bin","bytes":251748961,"fp16_bitwise_roundtrip":true,"fp16_payload_sha256":"4f6e54da228ef6a746cc2b14c39b045d8cc149fb27d955ddbd12bf6a36e88f9f","identity":{"actual_teacher_hf_revision":"9ce79652c1590997c8a3c84c420721774c90e363","cache_identity":"563bac05358fb4cb449e2b125d62a250dabded66e1cbe972801626c79359464a","checkpoint_path":"checkpoints/gch-e419-full-seed42-20261023-r1/checkpoint_step_359851.pt","checkpoint_sha256":"bded20ccb9fe69496ec55ebe3f630cef3d811c610353cf94944d322249a18a05","config_fingerprint":"a53fc42d105997e949fabf74a98f5ddb69a706da590803abbc07fb3eb349793b","dataset_fingerprint":"ccb6c5b7f1bddec623cd94a9fc146a4d268f35eaab666459de6b911732d4a32b","dataset_revision":"a1adc9749e294ccff4eaac376de1c78ef0ea33ca","extraction_git_commit":"a1ab5d28bb49b91aa4aafd8758b1c6d6e0c2f3eb","extraction_plan_fingerprint":"b1baaaa70695701f9dbd63db323b42d174a87f527c07e21053fe0fbc2f4d4fab","graph_enabled":true,"implementation_sha256":{"knowledge_batch_benchmark.py":"d1820d06951789fb4f891a87c51cf2467f6b66942dac59a4b6f12621adedecf0","knowledge_batching.py":"79fad817fb34fd2a65f1934c96bbc46ed856cd3333d112bcedd970bd9eb2b51f","knowledge_cpu_benchmark.py":"7799132ca843857aa574fb2ec98a906b9181c6080de377c37fc6fbaff6bad7ae","knowledge_cpu_profile.py":"b38dee1918bfcf3fcc37aefd1fd3077a294d19b3994212c91778b1acb27d3cd6","knowledge_engineering_benchmark.py":"ca255b151a75fc5df6be9565c5834be662f7bdf03dfea4bb812fdcad750b362b","knowledge_extraction.py":"b93fd25bdcdda7590c67f6a91e5cd0919b26d1b40decd52c3c4e823aa9396c7a","knowledge_full_pipeline.py":"0aca81dbbd0581c193c18fece95e3c6e7337223d10bb226af2a33a93edd7ad7c","knowledge_group_publication.py":"4c6e68612e67dce7a233ef26c2e6680353c68ececbfe332add06a2db76080406","knowledge_inference.py":"a08d5816628c887d63c121f9c65d7a3cd2e826fe66a31cc206f9a2c61ca3741e","knowledge_monitor.py":"d5374952b8cedb0a52f4c5e04f490a108e9a48e1062e4fd22b14cd68aa7f3ebd","knowledge_network_benchmark.py":"1346b3b5c7f959b7faa7cada563f1953b2c036653f689c7e6c88e268f847884a","knowledge_pipeline.py":"a421283f5115e710a7a8eafaa0725a3b3a3d394086067afd85a77eeedf04decb","knowledge_prefetch.py":"2da9ba2f717128f4e8199f5fa58cdbea3004cd662f875c29e03aa647a803ea4d","knowledge_production.py":"198d46406f8dbd5c37c7d478bb6e381dbab0a17afa693af1df00105fb40dc2db","knowledge_production_publication.py":"c1be2b97a84f1dc2df74926504dc914bff8fdca547dfb04c3f35143ba6e73254","knowledge_publication.py":"94e206a5d82066c3bf24ee803eec681d09cbbaf58d9efa879632ea96fc638f4e","knowledge_retry.py":"90d7da0c4e41e9a52904a8dafce462bc394218da276b72d1b8306cd480d6e3b6","knowledge_runtime_bundle.py":"9119c0dd7c1113211caac100ed4d263a6cd189ca589cc44d8c2d33fc43a6310d","knowledge_shard.py":"353c615df196f7ae6e68fba10b4a0d780c960c26dbc97a87469f004969ed2716","knowledge_source_prefetch.py":"662e5ebd2c0f18261eb24926c71128bef47cf5c04907d42a6e1c96b4775ace7a","knowledge_staging.py":"04476f37b5283fb806a07fa33b323848110fd5e8d128b29601fc910607497cff","knowledge_storage.py":"75569fb81878f3a30d0695e370b7d0085372cb461ea57f08e05651a608e59f7c","knowledge_stream_benchmark.py":"58813bbab04756c9608e2fabbc6035a62320170675246dc321b8369c4099e087","knowledge_teacher.py":"a1a7c2a5f9d98dba272253629a6b8880509cbcc70f05768e0b16b8f5c9cb8f43","knowledge_transport.py":"8abe7a81aa627a73cfead513834f415ab686a85073ef894f92faca8059fb2c61"},"limitations":["Parent producer/provenance/license-scope evidence remains unverified under issues 161 and 171.","Cross-split, near-duplicate and benchmark leakage checks remain unverified.","Published source/build plan is incomplete; full payload checksums have not been independently reproduced.","Author-reported payload observations are not independently reproduced research acceptance."],"metadata_sha256":{"resolved_config.json":"66b5da6f3336597d52bb8ab2b819941040f1b84d44344a06801bf0a1ae477f78","run.json":"ce1e369cf3dd6dc204aec8c9ab98c8bda1121291683f059bf5b12c8112da90f0","streaming_identity.json":"eff0460e7b26ccea0bce87e21cc26d04627fea883c3aeaf03d22550c701502a7"},"pipeline_version":2,"production_contract":{"batch_size":1024,"group_size":8,"layout":"packed_zstd1","queue_depth":8,"shard_rows":131072,"source_prefetch_depth":2},"runtime":{"cuda":"13.0","gpu":"NVIDIA RTX PRO 6000 Blackwell Server Edition","numpy":"2.2.6","precision":"bf16","pyarrow":"21.0.0","python":"3.13.11","recurrent_precision":"fp32","torch":"2.11.0+cu130"},"schema":{"channel_order":["form:0:5","tone:0:6","boundary:0:1","case:0:2"],"channels":14,"dtype":"<f2","logits":"final_post_graph_raw","padding_policy":"source_mask_true_only","schema_version":"graph_e1_raw_fp16_v1","split":"train","task_variant":"T2_JOINT","unsupported_policy":"retain_row_empty_logits"},"sealed_test_accessed":false,"source_manifest_sha256":"be0b123332b94fdad66f4c8bc9eb7c9fed93596b053d83e43581fb04398a3492","source_train_files_sha256":"eb3c1b65b844e1081a3ecf79065c12d6bc2b6a341b01dbfdacf120e4fbe6f279","strict_state_restore":true,"teacher_git_commit":"ae0250338a1ce4ea51c980f523a7e084ff668510","teacher_parameter_count":4236728,"teacher_run_id":"gch-e419-full-seed42-20261023-r1"},"layout":"packed_zstd1","raw_count":131072,"row_end":52297728,"row_start":52166656,"sha256":"d7e002046f875d7a04d2ae6081fae5795a539464181c77b6a338c48bb371fe04","shard":398,"state":"UPLOADED","supported_count":130895,"token_count":11631786,"unsupported_count":177}
|
knowledge/graph-e1-raw-fp16-v2/receipts/000399.json
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
{"alignment_sha256":"4cc285d279d24252515c51f9e03cb3f105ca6f84c22c9210108cf2886345c91e","artifact_path":"knowledge/graph-e1-raw-fp16-v2/shards/000399.bin","bytes":252151282,"fp16_bitwise_roundtrip":true,"fp16_payload_sha256":"3112807386cfa02c5b12727c5250213e529f100d59e250edd3d2f84a30e93ada","identity":{"actual_teacher_hf_revision":"9ce79652c1590997c8a3c84c420721774c90e363","cache_identity":"563bac05358fb4cb449e2b125d62a250dabded66e1cbe972801626c79359464a","checkpoint_path":"checkpoints/gch-e419-full-seed42-20261023-r1/checkpoint_step_359851.pt","checkpoint_sha256":"bded20ccb9fe69496ec55ebe3f630cef3d811c610353cf94944d322249a18a05","config_fingerprint":"a53fc42d105997e949fabf74a98f5ddb69a706da590803abbc07fb3eb349793b","dataset_fingerprint":"ccb6c5b7f1bddec623cd94a9fc146a4d268f35eaab666459de6b911732d4a32b","dataset_revision":"a1adc9749e294ccff4eaac376de1c78ef0ea33ca","extraction_git_commit":"a1ab5d28bb49b91aa4aafd8758b1c6d6e0c2f3eb","extraction_plan_fingerprint":"b1baaaa70695701f9dbd63db323b42d174a87f527c07e21053fe0fbc2f4d4fab","graph_enabled":true,"implementation_sha256":{"knowledge_batch_benchmark.py":"d1820d06951789fb4f891a87c51cf2467f6b66942dac59a4b6f12621adedecf0","knowledge_batching.py":"79fad817fb34fd2a65f1934c96bbc46ed856cd3333d112bcedd970bd9eb2b51f","knowledge_cpu_benchmark.py":"7799132ca843857aa574fb2ec98a906b9181c6080de377c37fc6fbaff6bad7ae","knowledge_cpu_profile.py":"b38dee1918bfcf3fcc37aefd1fd3077a294d19b3994212c91778b1acb27d3cd6","knowledge_engineering_benchmark.py":"ca255b151a75fc5df6be9565c5834be662f7bdf03dfea4bb812fdcad750b362b","knowledge_extraction.py":"b93fd25bdcdda7590c67f6a91e5cd0919b26d1b40decd52c3c4e823aa9396c7a","knowledge_full_pipeline.py":"0aca81dbbd0581c193c18fece95e3c6e7337223d10bb226af2a33a93edd7ad7c","knowledge_group_publication.py":"4c6e68612e67dce7a233ef26c2e6680353c68ececbfe332add06a2db76080406","knowledge_inference.py":"a08d5816628c887d63c121f9c65d7a3cd2e826fe66a31cc206f9a2c61ca3741e","knowledge_monitor.py":"d5374952b8cedb0a52f4c5e04f490a108e9a48e1062e4fd22b14cd68aa7f3ebd","knowledge_network_benchmark.py":"1346b3b5c7f959b7faa7cada563f1953b2c036653f689c7e6c88e268f847884a","knowledge_pipeline.py":"a421283f5115e710a7a8eafaa0725a3b3a3d394086067afd85a77eeedf04decb","knowledge_prefetch.py":"2da9ba2f717128f4e8199f5fa58cdbea3004cd662f875c29e03aa647a803ea4d","knowledge_production.py":"198d46406f8dbd5c37c7d478bb6e381dbab0a17afa693af1df00105fb40dc2db","knowledge_production_publication.py":"c1be2b97a84f1dc2df74926504dc914bff8fdca547dfb04c3f35143ba6e73254","knowledge_publication.py":"94e206a5d82066c3bf24ee803eec681d09cbbaf58d9efa879632ea96fc638f4e","knowledge_retry.py":"90d7da0c4e41e9a52904a8dafce462bc394218da276b72d1b8306cd480d6e3b6","knowledge_runtime_bundle.py":"9119c0dd7c1113211caac100ed4d263a6cd189ca589cc44d8c2d33fc43a6310d","knowledge_shard.py":"353c615df196f7ae6e68fba10b4a0d780c960c26dbc97a87469f004969ed2716","knowledge_source_prefetch.py":"662e5ebd2c0f18261eb24926c71128bef47cf5c04907d42a6e1c96b4775ace7a","knowledge_staging.py":"04476f37b5283fb806a07fa33b323848110fd5e8d128b29601fc910607497cff","knowledge_storage.py":"75569fb81878f3a30d0695e370b7d0085372cb461ea57f08e05651a608e59f7c","knowledge_stream_benchmark.py":"58813bbab04756c9608e2fabbc6035a62320170675246dc321b8369c4099e087","knowledge_teacher.py":"a1a7c2a5f9d98dba272253629a6b8880509cbcc70f05768e0b16b8f5c9cb8f43","knowledge_transport.py":"8abe7a81aa627a73cfead513834f415ab686a85073ef894f92faca8059fb2c61"},"limitations":["Parent producer/provenance/license-scope evidence remains unverified under issues 161 and 171.","Cross-split, near-duplicate and benchmark leakage checks remain unverified.","Published source/build plan is incomplete; full payload checksums have not been independently reproduced.","Author-reported payload observations are not independently reproduced research acceptance."],"metadata_sha256":{"resolved_config.json":"66b5da6f3336597d52bb8ab2b819941040f1b84d44344a06801bf0a1ae477f78","run.json":"ce1e369cf3dd6dc204aec8c9ab98c8bda1121291683f059bf5b12c8112da90f0","streaming_identity.json":"eff0460e7b26ccea0bce87e21cc26d04627fea883c3aeaf03d22550c701502a7"},"pipeline_version":2,"production_contract":{"batch_size":1024,"group_size":8,"layout":"packed_zstd1","queue_depth":8,"shard_rows":131072,"source_prefetch_depth":2},"runtime":{"cuda":"13.0","gpu":"NVIDIA RTX PRO 6000 Blackwell Server Edition","numpy":"2.2.6","precision":"bf16","pyarrow":"21.0.0","python":"3.13.11","recurrent_precision":"fp32","torch":"2.11.0+cu130"},"schema":{"channel_order":["form:0:5","tone:0:6","boundary:0:1","case:0:2"],"channels":14,"dtype":"<f2","logits":"final_post_graph_raw","padding_policy":"source_mask_true_only","schema_version":"graph_e1_raw_fp16_v1","split":"train","task_variant":"T2_JOINT","unsupported_policy":"retain_row_empty_logits"},"sealed_test_accessed":false,"source_manifest_sha256":"be0b123332b94fdad66f4c8bc9eb7c9fed93596b053d83e43581fb04398a3492","source_train_files_sha256":"eb3c1b65b844e1081a3ecf79065c12d6bc2b6a341b01dbfdacf120e4fbe6f279","strict_state_restore":true,"teacher_git_commit":"ae0250338a1ce4ea51c980f523a7e084ff668510","teacher_parameter_count":4236728,"teacher_run_id":"gch-e419-full-seed42-20261023-r1"},"layout":"packed_zstd1","raw_count":131072,"row_end":52428800,"row_start":52297728,"sha256":"21961c5d1caab70c18c61552f69959fdf155c908dffbb51d860c23ae4544f6c6","shard":399,"state":"UPLOADED","supported_count":130908,"token_count":11650658,"unsupported_count":164}
|
knowledge/graph-e1-raw-fp16-v2/shards/000392.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:7d970ea3ae92294c9b136a224edd202e135a3cdbcf3dedd56854e3161214c733
|
| 3 |
+
size 252238054
|
knowledge/graph-e1-raw-fp16-v2/shards/000393.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:a04ef4ffa35aac37acf6ef035d907622a256f7eb193b76fa6d0538322ceffa49
|
| 3 |
+
size 251365322
|
knowledge/graph-e1-raw-fp16-v2/shards/000394.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:a4df05071997ecf3a07d5372a866b28c2efc42f965e0aeaa7886eab07801e355
|
| 3 |
+
size 251399524
|
knowledge/graph-e1-raw-fp16-v2/shards/000395.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:be8b7b45ce5f7246a42d173db7ea218f3775ac013ca5c3570ec8e4908fedc1ed
|
| 3 |
+
size 252014210
|
knowledge/graph-e1-raw-fp16-v2/shards/000396.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:6b03d189f32fc0cbddcf5dc439422c013dd378ce56ba886122d4ff6eddd9f3de
|
| 3 |
+
size 252187763
|
knowledge/graph-e1-raw-fp16-v2/shards/000397.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:e95c2a778fac9a6a95a64df8b65eaf4fb2f71a6a66f8e44721cadde92d6da1ef
|
| 3 |
+
size 251995107
|
knowledge/graph-e1-raw-fp16-v2/shards/000398.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:d7e002046f875d7a04d2ae6081fae5795a539464181c77b6a338c48bb371fe04
|
| 3 |
+
size 251748961
|
knowledge/graph-e1-raw-fp16-v2/shards/000399.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:21961c5d1caab70c18c61552f69959fdf155c908dffbb51d860c23ae4544f6c6
|
| 3 |
+
size 252151282
|