knowledge: upload immutable shard group
Browse files- knowledge/graph-e1-raw-fp16-v2/receipts/000168.json +1 -0
- knowledge/graph-e1-raw-fp16-v2/receipts/000169.json +1 -0
- knowledge/graph-e1-raw-fp16-v2/receipts/000170.json +1 -0
- knowledge/graph-e1-raw-fp16-v2/receipts/000171.json +1 -0
- knowledge/graph-e1-raw-fp16-v2/receipts/000172.json +1 -0
- knowledge/graph-e1-raw-fp16-v2/receipts/000173.json +1 -0
- knowledge/graph-e1-raw-fp16-v2/receipts/000174.json +1 -0
- knowledge/graph-e1-raw-fp16-v2/receipts/000175.json +1 -0
- knowledge/graph-e1-raw-fp16-v2/shards/000168.bin +3 -0
- knowledge/graph-e1-raw-fp16-v2/shards/000169.bin +3 -0
- knowledge/graph-e1-raw-fp16-v2/shards/000170.bin +3 -0
- knowledge/graph-e1-raw-fp16-v2/shards/000171.bin +3 -0
- knowledge/graph-e1-raw-fp16-v2/shards/000172.bin +3 -0
- knowledge/graph-e1-raw-fp16-v2/shards/000173.bin +3 -0
- knowledge/graph-e1-raw-fp16-v2/shards/000174.bin +3 -0
- knowledge/graph-e1-raw-fp16-v2/shards/000175.bin +3 -0
knowledge/graph-e1-raw-fp16-v2/receipts/000168.json
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{"alignment_sha256":"9c78e0ed81f13d09c9a1192da18df8d48fbbeee9a5e53817be06bc41f12d5f00","artifact_path":"knowledge/graph-e1-raw-fp16-v2/shards/000168.bin","bytes":251551238,"fp16_bitwise_roundtrip":true,"fp16_payload_sha256":"b9729bd2572428c6ba0e77a21aa9652faeb01605c064084af79e318328f9b0aa","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":22151168,"row_start":22020096,"sha256":"a0e16e3d0a0a9d933a3211b3af163fc9497f0fba770328a796b2ea9fa9ec160b","shard":168,"state":"UPLOADED","supported_count":130923,"token_count":11622760,"unsupported_count":149}
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knowledge/graph-e1-raw-fp16-v2/receipts/000169.json
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{"alignment_sha256":"af20b0b9e2c5d140c7a69d37def10bf5f1884c2a7f6087993d7c8648745980ea","artifact_path":"knowledge/graph-e1-raw-fp16-v2/shards/000169.bin","bytes":251730342,"fp16_bitwise_roundtrip":true,"fp16_payload_sha256":"477f7c883c0294e2554a5deb668312c2b5cdf11c2e3d9b6a301d2e1c0e20a641","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":22282240,"row_start":22151168,"sha256":"2fcd34436a445d159fc68f5f60b42afc35ff4ec9bd7c429e4bd280abf02c4072","shard":169,"state":"UPLOADED","supported_count":130916,"token_count":11631458,"unsupported_count":156}
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knowledge/graph-e1-raw-fp16-v2/receipts/000170.json
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{"alignment_sha256":"d6420c41f0670321d8016207fb49b38820ceed4d5dd69310b000bad5556dacd1","artifact_path":"knowledge/graph-e1-raw-fp16-v2/shards/000170.bin","bytes":251855930,"fp16_bitwise_roundtrip":true,"fp16_payload_sha256":"90c5f5412b7790d9da7f63a14211a4859695769dd4be8f53ffb49326f4afbacb","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":22413312,"row_start":22282240,"sha256":"08ca58c17124862122ad3c423192ce5ecec06b0d11de16632909e749a48b8b23","shard":170,"state":"UPLOADED","supported_count":130907,"token_count":11637099,"unsupported_count":165}
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knowledge/graph-e1-raw-fp16-v2/receipts/000171.json
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|
knowledge/graph-e1-raw-fp16-v2/receipts/000172.json
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{"alignment_sha256":"f7761097b7432785da24b27a89fb11d889696122fc262eb0d972ed665904a29a","artifact_path":"knowledge/graph-e1-raw-fp16-v2/shards/000172.bin","bytes":251518450,"fp16_bitwise_roundtrip":true,"fp16_payload_sha256":"2da40cd720cc6f435901877ade0c0722c0314adaed9a2382587f6ff9fecac102","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/000173.json
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{"alignment_sha256":"1f82d9d907f0e7127402b3ae2dd5e2875047fe08e76f11fd8667f5233ed4fbed","artifact_path":"knowledge/graph-e1-raw-fp16-v2/shards/000173.bin","bytes":252060380,"fp16_bitwise_roundtrip":true,"fp16_payload_sha256":"e2ce464add2fb9c18a8dbd3c5670462f2a3a384d2e9af3251325f6a1df005e93","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/000174.json
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