knowledge: upload immutable shard group
Browse files- knowledge/graph-e1-raw-fp16-v2/receipts/001296.json +1 -0
- knowledge/graph-e1-raw-fp16-v2/receipts/001297.json +1 -0
- knowledge/graph-e1-raw-fp16-v2/receipts/001298.json +1 -0
- knowledge/graph-e1-raw-fp16-v2/receipts/001299.json +1 -0
- knowledge/graph-e1-raw-fp16-v2/receipts/001300.json +1 -0
- knowledge/graph-e1-raw-fp16-v2/receipts/001301.json +1 -0
- knowledge/graph-e1-raw-fp16-v2/receipts/001302.json +1 -0
- knowledge/graph-e1-raw-fp16-v2/receipts/001303.json +1 -0
- knowledge/graph-e1-raw-fp16-v2/shards/001296.bin +3 -0
- knowledge/graph-e1-raw-fp16-v2/shards/001297.bin +3 -0
- knowledge/graph-e1-raw-fp16-v2/shards/001298.bin +3 -0
- knowledge/graph-e1-raw-fp16-v2/shards/001299.bin +3 -0
- knowledge/graph-e1-raw-fp16-v2/shards/001300.bin +3 -0
- knowledge/graph-e1-raw-fp16-v2/shards/001301.bin +3 -0
- knowledge/graph-e1-raw-fp16-v2/shards/001302.bin +3 -0
- knowledge/graph-e1-raw-fp16-v2/shards/001303.bin +3 -0
knowledge/graph-e1-raw-fp16-v2/receipts/001296.json
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{"alignment_sha256":"634e12224f01ff309df9d8faefd7bcea82cc46de5d4c34a5f4cac6eaae0135bb","artifact_path":"knowledge/graph-e1-raw-fp16-v2/shards/001296.bin","bytes":251951924,"fp16_bitwise_roundtrip":true,"fp16_payload_sha256":"963e7e188f8896d4640ee7d3a5eb55c50e3dae98b3944fa7d7bc68d30b47ffd1","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":170000384,"row_start":169869312,"sha256":"5c77999a20f7f6e81102e8db3677e0c70bf7a2e0eadeb748b94e0c8ceb995985","shard":1296,"state":"UPLOADED","supported_count":130919,"token_count":11641406,"unsupported_count":153}
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knowledge/graph-e1-raw-fp16-v2/receipts/001297.json
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{"alignment_sha256":"e39980b26f5fbd0aa230c22da4416b800d487c8e11a4fa2ddb215c5595975d19","artifact_path":"knowledge/graph-e1-raw-fp16-v2/shards/001297.bin","bytes":251598981,"fp16_bitwise_roundtrip":true,"fp16_payload_sha256":"2bf478d69d7a6706b4d2bf36ab5874437d8ec95ac61217a9e3c6dbea9c3058e3","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":170131456,"row_start":170000384,"sha256":"f33ec592cb0ea5f53f56ba4213fcab7fd71d1b91b012c8600f9ac889f10c05b4","shard":1297,"state":"UPLOADED","supported_count":130920,"token_count":11625081,"unsupported_count":152}
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knowledge/graph-e1-raw-fp16-v2/receipts/001298.json
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{"alignment_sha256":"571614d0c2006f9029ab47d201e03b80aa8fce47fbed71b83cf377ccdbfcaeee","artifact_path":"knowledge/graph-e1-raw-fp16-v2/shards/001298.bin","bytes":252365972,"fp16_bitwise_roundtrip":true,"fp16_payload_sha256":"3178c1379645707b924d752f7fe853f9754b884d9a78f2f3c725b4b13ab57fc4","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":170262528,"row_start":170131456,"sha256":"2be179e7522ad7343b965e64a15c27c1143a5ba90fef9a9fdc0756be16a8fc92","shard":1298,"state":"UPLOADED","supported_count":130923,"token_count":11660563,"unsupported_count":149}
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knowledge/graph-e1-raw-fp16-v2/receipts/001299.json
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|
knowledge/graph-e1-raw-fp16-v2/receipts/001300.json
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| 1 |
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{"alignment_sha256":"d6d648fa617ce67a9f08163a10aaa90b5013dbe9104f7b19bb39ff13e95e8211","artifact_path":"knowledge/graph-e1-raw-fp16-v2/shards/001300.bin","bytes":251645258,"fp16_bitwise_roundtrip":true,"fp16_payload_sha256":"9a06ffe2cad5ccdeeea673097c9b512c27f44b94a76e4eaa515ca450e87c967b","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; 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|
knowledge/graph-e1-raw-fp16-v2/receipts/001301.json
ADDED
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{"alignment_sha256":"5e4675eb3ed570450b82a9519f2aa06e1aa1474c4c32c9c86c9bb9305a2f68d7","artifact_path":"knowledge/graph-e1-raw-fp16-v2/shards/001301.bin","bytes":252071008,"fp16_bitwise_roundtrip":true,"fp16_payload_sha256":"5512f10a9e35f0ad5a5ed02daa411d16b503b82bc6330d68cf332c034f403ca9","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; 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|
knowledge/graph-e1-raw-fp16-v2/receipts/001302.json
ADDED
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| 1 |
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