[heartbeat] starting: bash /home/fedora/q7_datasets.sh
[heartbeat] interval: 60s
[heartbeat] label:    bash
+ R=/home/fedora/results/p0/q7
+ mkdir -p /home/fedora/results/p0/q7 /data/vdb
+ cd /data/vdb
+ B=https://assets.zilliz.com/benchmark
+ for u in http://ann-benchmarks.com/cohere-wikipedia-22-12-1M-angular.hdf5 https://ann-benchmarks.com/cohere-wikipedia-22-12-1M-angular.hdf5 http://ann-benchmarks.com/glove-100-angular.hdf5 https://huggingface.co/datasets/Cohere/wikipedia-22-12-en-embeddings https://huggingface.co/api/datasets/CohereLabs/wikipedia-2023-11-embed-multilingual-v3
++ curl -sL -o /dev/null --max-time 30 -w '%{http_code}' http://ann-benchmarks.com/cohere-wikipedia-22-12-1M-angular.hdf5
+ echo 'http://ann-benchmarks.com/cohere-wikipedia-22-12-1M-angular.hdf5 404'
+ for u in http://ann-benchmarks.com/cohere-wikipedia-22-12-1M-angular.hdf5 https://ann-benchmarks.com/cohere-wikipedia-22-12-1M-angular.hdf5 http://ann-benchmarks.com/glove-100-angular.hdf5 https://huggingface.co/datasets/Cohere/wikipedia-22-12-en-embeddings https://huggingface.co/api/datasets/CohereLabs/wikipedia-2023-11-embed-multilingual-v3
++ curl -sL -o /dev/null --max-time 30 -w '%{http_code}' https://ann-benchmarks.com/cohere-wikipedia-22-12-1M-angular.hdf5
+ echo 'https://ann-benchmarks.com/cohere-wikipedia-22-12-1M-angular.hdf5 404'
+ for u in http://ann-benchmarks.com/cohere-wikipedia-22-12-1M-angular.hdf5 https://ann-benchmarks.com/cohere-wikipedia-22-12-1M-angular.hdf5 http://ann-benchmarks.com/glove-100-angular.hdf5 https://huggingface.co/datasets/Cohere/wikipedia-22-12-en-embeddings https://huggingface.co/api/datasets/CohereLabs/wikipedia-2023-11-embed-multilingual-v3
++ curl -sL -o /dev/null --max-time 30 -w '%{http_code}' http://ann-benchmarks.com/glove-100-angular.hdf5
+ echo 'http://ann-benchmarks.com/glove-100-angular.hdf5 200'
+ for u in http://ann-benchmarks.com/cohere-wikipedia-22-12-1M-angular.hdf5 https://ann-benchmarks.com/cohere-wikipedia-22-12-1M-angular.hdf5 http://ann-benchmarks.com/glove-100-angular.hdf5 https://huggingface.co/datasets/Cohere/wikipedia-22-12-en-embeddings https://huggingface.co/api/datasets/CohereLabs/wikipedia-2023-11-embed-multilingual-v3
++ curl -sL -o /dev/null --max-time 30 -w '%{http_code}' https://huggingface.co/datasets/Cohere/wikipedia-22-12-en-embeddings
+ echo 'https://huggingface.co/datasets/Cohere/wikipedia-22-12-en-embeddings 401'
+ for u in http://ann-benchmarks.com/cohere-wikipedia-22-12-1M-angular.hdf5 https://ann-benchmarks.com/cohere-wikipedia-22-12-1M-angular.hdf5 http://ann-benchmarks.com/glove-100-angular.hdf5 https://huggingface.co/datasets/Cohere/wikipedia-22-12-en-embeddings https://huggingface.co/api/datasets/CohereLabs/wikipedia-2023-11-embed-multilingual-v3
++ curl -sL -o /dev/null --max-time 30 -w '%{http_code}' https://huggingface.co/api/datasets/CohereLabs/wikipedia-2023-11-embed-multilingual-v3
+ echo 'https://huggingface.co/api/datasets/CohereLabs/wikipedia-2023-11-embed-multilingual-v3 200'
+ for d in cohere_medium_1m cohere_large_10m openai_large_5m
+ mkdir -p cohere_medium_1m
+ for f in test.parquet neighbors.parquet
+ curl -s -C - -o cohere_medium_1m/test.parquet https://assets.zilliz.com/benchmark/cohere_medium_1m/test.parquet
+ for f in test.parquet neighbors.parquet
+ curl -s -C - -o cohere_medium_1m/neighbors.parquet https://assets.zilliz.com/benchmark/cohere_medium_1m/neighbors.parquet
++ seq 0 9
+ for i in $(seq 0 9)
+ f=train-00-of-10.parquet
++ curl -sI https://assets.zilliz.com/benchmark/cohere_medium_1m/train-00-of-10.parquet
++ tr -d '\r'
++ awk 'tolower($1)=="content-length:"{l=$2} tolower($1)=="etag:"{e=$2} END{print l, e}'
+ echo 'cohere_medium_1m/train-00-of-10.parquet  '
+ for i in $(seq 0 9)
+ f=train-01-of-10.parquet
++ curl -sI https://assets.zilliz.com/benchmark/cohere_medium_1m/train-01-of-10.parquet
++ tr -d '\r'
++ awk 'tolower($1)=="content-length:"{l=$2} tolower($1)=="etag:"{e=$2} END{print l, e}'
+ echo 'cohere_medium_1m/train-01-of-10.parquet  '
+ for i in $(seq 0 9)
+ f=train-02-of-10.parquet
++ curl -sI https://assets.zilliz.com/benchmark/cohere_medium_1m/train-02-of-10.parquet
++ tr -d '\r'
++ awk 'tolower($1)=="content-length:"{l=$2} tolower($1)=="etag:"{e=$2} END{print l, e}'
+ echo 'cohere_medium_1m/train-02-of-10.parquet  '
+ for i in $(seq 0 9)
+ f=train-03-of-10.parquet
++ curl -sI https://assets.zilliz.com/benchmark/cohere_medium_1m/train-03-of-10.parquet
++ tr -d '\r'
++ awk 'tolower($1)=="content-length:"{l=$2} tolower($1)=="etag:"{e=$2} END{print l, e}'
+ echo 'cohere_medium_1m/train-03-of-10.parquet  '
+ for i in $(seq 0 9)
+ f=train-04-of-10.parquet
++ curl -sI https://assets.zilliz.com/benchmark/cohere_medium_1m/train-04-of-10.parquet
++ tr -d '\r'
++ awk 'tolower($1)=="content-length:"{l=$2} tolower($1)=="etag:"{e=$2} END{print l, e}'
+ echo 'cohere_medium_1m/train-04-of-10.parquet  '
+ for i in $(seq 0 9)
+ f=train-05-of-10.parquet
++ curl -sI https://assets.zilliz.com/benchmark/cohere_medium_1m/train-05-of-10.parquet
++ tr -d '\r'
++ awk 'tolower($1)=="content-length:"{l=$2} tolower($1)=="etag:"{e=$2} END{print l, e}'
+ echo 'cohere_medium_1m/train-05-of-10.parquet  '
+ for i in $(seq 0 9)
+ f=train-06-of-10.parquet
++ curl -sI https://assets.zilliz.com/benchmark/cohere_medium_1m/train-06-of-10.parquet
++ tr -d '\r'
++ awk 'tolower($1)=="content-length:"{l=$2} tolower($1)=="etag:"{e=$2} END{print l, e}'
+ echo 'cohere_medium_1m/train-06-of-10.parquet  '
+ for i in $(seq 0 9)
+ f=train-07-of-10.parquet
++ curl -sI https://assets.zilliz.com/benchmark/cohere_medium_1m/train-07-of-10.parquet
++ tr -d '\r'
++ awk 'tolower($1)=="content-length:"{l=$2} tolower($1)=="etag:"{e=$2} END{print l, e}'
+ echo 'cohere_medium_1m/train-07-of-10.parquet  '
+ for i in $(seq 0 9)
+ f=train-08-of-10.parquet
++ curl -sI https://assets.zilliz.com/benchmark/cohere_medium_1m/train-08-of-10.parquet
++ tr -d '\r'
++ awk 'tolower($1)=="content-length:"{l=$2} tolower($1)=="etag:"{e=$2} END{print l, e}'
+ echo 'cohere_medium_1m/train-08-of-10.parquet  '
+ for i in $(seq 0 9)
+ f=train-09-of-10.parquet
++ curl -sI https://assets.zilliz.com/benchmark/cohere_medium_1m/train-09-of-10.parquet
++ tr -d '\r'
++ awk 'tolower($1)=="content-length:"{l=$2} tolower($1)=="etag:"{e=$2} END{print l, e}'
+ echo 'cohere_medium_1m/train-09-of-10.parquet  '
++ curl -sI https://assets.zilliz.com/benchmark/cohere_medium_1m/train.parquet
++ tr -d '\r'
++ awk 'tolower($1)=="content-length:"{l=$2} tolower($1)=="etag:"{e=$2} END{print l, e}'
+ echo 'cohere_medium_1m/train.parquet 3131995162 "9f40b7c484423428d5c4dbade66b0e31-374"'
+ for d in cohere_medium_1m cohere_large_10m openai_large_5m
+ mkdir -p cohere_large_10m
+ for f in test.parquet neighbors.parquet
+ curl -s -C - -o cohere_large_10m/test.parquet https://assets.zilliz.com/benchmark/cohere_large_10m/test.parquet
+ for f in test.parquet neighbors.parquet
+ curl -s -C - -o cohere_large_10m/neighbors.parquet https://assets.zilliz.com/benchmark/cohere_large_10m/neighbors.parquet
++ seq 0 9
+ for i in $(seq 0 9)
+ f=train-00-of-10.parquet
++ curl -sI https://assets.zilliz.com/benchmark/cohere_large_10m/train-00-of-10.parquet
++ tr -d '\r'
++ awk 'tolower($1)=="content-length:"{l=$2} tolower($1)=="etag:"{e=$2} END{print l, e}'
+ echo 'cohere_large_10m/train-00-of-10.parquet 3132712656 "fa67c7cffb98c268625d480ab1de8fa3-374"'
+ for i in $(seq 0 9)
+ f=train-01-of-10.parquet
++ curl -sI https://assets.zilliz.com/benchmark/cohere_large_10m/train-01-of-10.parquet
++ tr -d '\r'
++ awk 'tolower($1)=="content-length:"{l=$2} tolower($1)=="etag:"{e=$2} END{print l, e}'
+ echo 'cohere_large_10m/train-01-of-10.parquet 3132688995 "1e09a7e47e277e35a30b2e0e6e3a4beb-374"'
+ for i in $(seq 0 9)
+ f=train-02-of-10.parquet
++ curl -sI https://assets.zilliz.com/benchmark/cohere_large_10m/train-02-of-10.parquet
++ tr -d '\r'
++ awk 'tolower($1)=="content-length:"{l=$2} tolower($1)=="etag:"{e=$2} END{print l, e}'
+ echo 'cohere_large_10m/train-02-of-10.parquet 3132687596 "e1eb2854d008db53e2204b682bddb55d-374"'
+ for i in $(seq 0 9)
+ f=train-03-of-10.parquet
++ curl -sI https://assets.zilliz.com/benchmark/cohere_large_10m/train-03-of-10.parquet
++ tr -d '\r'
++ awk 'tolower($1)=="content-length:"{l=$2} tolower($1)=="etag:"{e=$2} END{print l, e}'
+ echo 'cohere_large_10m/train-03-of-10.parquet 3132679477 "7922f6efabf9a7b6e07a9b1533dc0bf1-374"'
+ for i in $(seq 0 9)
+ f=train-04-of-10.parquet
++ curl -sI https://assets.zilliz.com/benchmark/cohere_large_10m/train-04-of-10.parquet
++ tr -d '\r'
++ awk 'tolower($1)=="content-length:"{l=$2} tolower($1)=="etag:"{e=$2} END{print l, e}'
+ echo 'cohere_large_10m/train-04-of-10.parquet 3132702312 "ccee8e54b646123b986cb2766fa25a5a-374"'
+ for i in $(seq 0 9)
+ f=train-05-of-10.parquet
++ curl -sI https://assets.zilliz.com/benchmark/cohere_large_10m/train-05-of-10.parquet
++ tr -d '\r'
++ awk 'tolower($1)=="content-length:"{l=$2} tolower($1)=="etag:"{e=$2} END{print l, e}'
+ echo 'cohere_large_10m/train-05-of-10.parquet 3132683521 "d3bd2a8a358fb6f1925284b66528780b-374"'
+ for i in $(seq 0 9)
+ f=train-06-of-10.parquet
++ curl -sI https://assets.zilliz.com/benchmark/cohere_large_10m/train-06-of-10.parquet
++ tr -d '\r'
++ awk 'tolower($1)=="content-length:"{l=$2} tolower($1)=="etag:"{e=$2} END{print l, e}'
+ echo 'cohere_large_10m/train-06-of-10.parquet 3132691091 "6ddaa047e7f563bd55f07fb2dfe95450-374"'
+ for i in $(seq 0 9)
+ f=train-07-of-10.parquet
++ curl -sI https://assets.zilliz.com/benchmark/cohere_large_10m/train-07-of-10.parquet
++ tr -d '\r'
++ awk 'tolower($1)=="content-length:"{l=$2} tolower($1)=="etag:"{e=$2} END{print l, e}'
+ echo 'cohere_large_10m/train-07-of-10.parquet 3132692641 "425ef3e83380ed6076e2b0e0e4b60e97-374"'
+ for i in $(seq 0 9)
+ f=train-08-of-10.parquet
++ curl -sI https://assets.zilliz.com/benchmark/cohere_large_10m/train-08-of-10.parquet
++ tr -d '\r'
++ awk 'tolower($1)=="content-length:"{l=$2} tolower($1)=="etag:"{e=$2} END{print l, e}'
+ echo 'cohere_large_10m/train-08-of-10.parquet 3132694246 "87411bafc73861764209bc3328dda21b-374"'
+ for i in $(seq 0 9)
+ f=train-09-of-10.parquet
++ curl -sI https://assets.zilliz.com/benchmark/cohere_large_10m/train-09-of-10.parquet
++ tr -d '\r'
++ awk 'tolower($1)=="content-length:"{l=$2} tolower($1)=="etag:"{e=$2} END{print l, e}'
+ echo 'cohere_large_10m/train-09-of-10.parquet 3132706678 "ab9e966c1193d0bd5c5cdecb9bc7c424-374"'
++ curl -sI https://assets.zilliz.com/benchmark/cohere_large_10m/train.parquet
++ tr -d '\r'
++ awk 'tolower($1)=="content-length:"{l=$2} tolower($1)=="etag:"{e=$2} END{print l, e}'
+ echo 'cohere_large_10m/train.parquet  '
+ for d in cohere_medium_1m cohere_large_10m openai_large_5m
+ mkdir -p openai_large_5m
+ for f in test.parquet neighbors.parquet
+ curl -s -C - -o openai_large_5m/test.parquet https://assets.zilliz.com/benchmark/openai_large_5m/test.parquet
+ for f in test.parquet neighbors.parquet
+ curl -s -C - -o openai_large_5m/neighbors.parquet https://assets.zilliz.com/benchmark/openai_large_5m/neighbors.parquet
++ seq 0 9
+ for i in $(seq 0 9)
+ f=train-00-of-10.parquet
++ curl -sI https://assets.zilliz.com/benchmark/openai_large_5m/train-00-of-10.parquet
++ tr -d '\r'
++ awk 'tolower($1)=="content-length:"{l=$2} tolower($1)=="etag:"{e=$2} END{print l, e}'
+ echo 'openai_large_5m/train-00-of-10.parquet 4494434813 "cdc4307b9d09993d08c7023a7c035c6b-536"'
+ for i in $(seq 0 9)
+ f=train-01-of-10.parquet
++ curl -sI https://assets.zilliz.com/benchmark/openai_large_5m/train-01-of-10.parquet
++ tr -d '\r'
++ awk 'tolower($1)=="content-length:"{l=$2} tolower($1)=="etag:"{e=$2} END{print l, e}'
+ echo 'openai_large_5m/train-01-of-10.parquet 4494470993 "8a5ac7812447cd4666a8953cfc5efd44-536"'
+ for i in $(seq 0 9)
+ f=train-02-of-10.parquet
++ curl -sI https://assets.zilliz.com/benchmark/openai_large_5m/train-02-of-10.parquet
++ tr -d '\r'
++ awk 'tolower($1)=="content-length:"{l=$2} tolower($1)=="etag:"{e=$2} END{print l, e}'
+ echo 'openai_large_5m/train-02-of-10.parquet 4494421533 "87ba66c060269dac5cbbc8aaa7b9be11-536"'
+ for i in $(seq 0 9)
+ f=train-03-of-10.parquet
++ curl -sI https://assets.zilliz.com/benchmark/openai_large_5m/train-03-of-10.parquet
++ tr -d '\r'
++ awk 'tolower($1)=="content-length:"{l=$2} tolower($1)=="etag:"{e=$2} END{print l, e}'
+ echo 'openai_large_5m/train-03-of-10.parquet 4494494836 "ed0ccf7f88febdd3158eaf26cda6bcfd-536"'
+ for i in $(seq 0 9)
+ f=train-04-of-10.parquet
++ curl -sI https://assets.zilliz.com/benchmark/openai_large_5m/train-04-of-10.parquet
++ tr -d '\r'
++ awk 'tolower($1)=="content-length:"{l=$2} tolower($1)=="etag:"{e=$2} END{print l, e}'
+ echo 'openai_large_5m/train-04-of-10.parquet 4494461722 "719258b96169875c1bba6bfaff460d14-536"'
+ for i in $(seq 0 9)
+ f=train-05-of-10.parquet
++ curl -sI https://assets.zilliz.com/benchmark/openai_large_5m/train-05-of-10.parquet
++ tr -d '\r'
++ awk 'tolower($1)=="content-length:"{l=$2} tolower($1)=="etag:"{e=$2} END{print l, e}'
+ echo 'openai_large_5m/train-05-of-10.parquet 4494402480 "0452ce7604d7937f2578543d2dad039a-536"'
+ for i in $(seq 0 9)
+ f=train-06-of-10.parquet
++ curl -sI https://assets.zilliz.com/benchmark/openai_large_5m/train-06-of-10.parquet
++ tr -d '\r'
++ awk 'tolower($1)=="content-length:"{l=$2} tolower($1)=="etag:"{e=$2} END{print l, e}'
+ echo 'openai_large_5m/train-06-of-10.parquet 4494430804 "53fc16a1ff9c9f018b6b10cab31fa9f0-536"'
+ for i in $(seq 0 9)
+ f=train-07-of-10.parquet
++ curl -sI https://assets.zilliz.com/benchmark/openai_large_5m/train-07-of-10.parquet
++ tr -d '\r'
++ awk 'tolower($1)=="content-length:"{l=$2} tolower($1)=="etag:"{e=$2} END{print l, e}'
+ echo 'openai_large_5m/train-07-of-10.parquet 4494392488 "ec5ebfc01164de9f44940f091bc7c599-536"'
+ for i in $(seq 0 9)
+ f=train-08-of-10.parquet
++ curl -sI https://assets.zilliz.com/benchmark/openai_large_5m/train-08-of-10.parquet
++ tr -d '\r'
++ awk 'tolower($1)=="content-length:"{l=$2} tolower($1)=="etag:"{e=$2} END{print l, e}'
+ echo 'openai_large_5m/train-08-of-10.parquet 4494458560 "66271ad22495d6bf6a8ec97a9e5cc82e-536"'
+ for i in $(seq 0 9)
+ f=train-09-of-10.parquet
++ curl -sI https://assets.zilliz.com/benchmark/openai_large_5m/train-09-of-10.parquet
++ tr -d '\r'
++ awk 'tolower($1)=="content-length:"{l=$2} tolower($1)=="etag:"{e=$2} END{print l, e}'
+ echo 'openai_large_5m/train-09-of-10.parquet 4494350061 "687e782ad57b698e366ae46086e1b2b3-536"'
++ curl -sI https://assets.zilliz.com/benchmark/openai_large_5m/train.parquet
++ tr -d '\r'
++ awk 'tolower($1)=="content-length:"{l=$2} tolower($1)=="etag:"{e=$2} END{print l, e}'
+ echo 'openai_large_5m/train.parquet  '
+ curl -s -o cohere_medium_1m/train.parquet https://assets.zilliz.com/benchmark/cohere_medium_1m/train.parquet
. [bash 19:38:40 elapsed]
. [bash 19:39:40 elapsed]
. [bash 19:40:40 elapsed]
. [bash 19:41:40 elapsed]
. [bash 19:42:40 elapsed]
. [bash 19:43:40 elapsed]
. [bash 19:44:40 elapsed]
. [bash 19:45:40 elapsed]
. [bash 19:46:40 elapsed]
. [bash 19:47:40 elapsed]
+ md5sum cohere_large_10m/neighbors.parquet cohere_large_10m/test.parquet cohere_medium_1m/neighbors.parquet cohere_medium_1m/test.parquet cohere_medium_1m/train.parquet openai_large_5m/neighbors.parquet openai_large_5m/test.parquet
+ python3 -
. [bash 19:48:40 elapsed]
+ cat /home/fedora/results/p0/q7/url_status.txt /home/fedora/results/p0/q7/vdb_counts.txt /home/fedora/results/p0/q7/vdb_md5.txt /home/fedora/results/p0/q7/vdb_train_heads.txt
http://ann-benchmarks.com/cohere-wikipedia-22-12-1M-angular.hdf5 404
https://ann-benchmarks.com/cohere-wikipedia-22-12-1M-angular.hdf5 404
http://ann-benchmarks.com/glove-100-angular.hdf5 200
https://huggingface.co/datasets/Cohere/wikipedia-22-12-en-embeddings 401
https://huggingface.co/api/datasets/CohereLabs/wikipedia-2023-11-embed-multilingual-v3 200
/data/vdb/cohere_large_10m/neighbors.parquet rows 1000 schema id: int64
neighbors_id: large_list<item: int64>
  child 0, item: int64
/data/vdb/cohere_large_10m/test.parquet rows 1000 schema id: int64
emb: large_list<item: float>
  child 0, item: float
/data/vdb/cohere_medium_1m/neighbors.parquet rows 1000 schema id: int64
neighbors_id: large_list<item: int64>
  child 0, item: int64
/data/vdb/cohere_medium_1m/test.parquet rows 1000 schema id: int64
emb: large_list<item: float>
  child 0, item: float
/data/vdb/cohere_medium_1m/train.parquet rows 1000000 schema id: int64
emb: large_list<item: float>
  child 0, item: float
/data/vdb/openai_large_5m/neighbors.parquet rows 1000 schema id: int64
neighbors_id: list<item: int64>
  child 0, item: int64
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 491
/data/vdb/openai_large_5m/test.parquet rows 1000 schema id: int64
emb: large_list<item: double>
  child 0, item: double
cohere_medium_1m: test (1000, 768) train (1000000, 768)
norms test min/max 12.342849 16.224667 train min/max 12.258187 17.474176
corpus exact-dup rows (after normalise): 81  test queries exactly equal to a corpus row: 1
test queries with max cos >= 1-1e-6: 1  >= 0.9999: 1
ed8a95682c184a5ad3de2538e64e189c  cohere_large_10m/neighbors.parquet
293629678416c4e1b8076e45d17ba569  cohere_large_10m/test.parquet
d1aca052763a292b10e80bbda964f55d  cohere_medium_1m/neighbors.parquet
c63a0efd0e611d9f35345af1fc6f7966  cohere_medium_1m/test.parquet
51f7420cc71b6de7f7218d2dc1eb983f  cohere_medium_1m/train.parquet
072e4fa27dcb4c116485367d06c6f1a4  openai_large_5m/neighbors.parquet
392273730a5f6a8893acca3f4d6d8a9b  openai_large_5m/test.parquet
cohere_medium_1m/train-00-of-10.parquet  
cohere_medium_1m/train-01-of-10.parquet  
cohere_medium_1m/train-02-of-10.parquet  
cohere_medium_1m/train-03-of-10.parquet  
cohere_medium_1m/train-04-of-10.parquet  
cohere_medium_1m/train-05-of-10.parquet  
cohere_medium_1m/train-06-of-10.parquet  
cohere_medium_1m/train-07-of-10.parquet  
cohere_medium_1m/train-08-of-10.parquet  
cohere_medium_1m/train-09-of-10.parquet  
cohere_medium_1m/train.parquet 3131995162 "9f40b7c484423428d5c4dbade66b0e31-374"
cohere_large_10m/train-00-of-10.parquet 3132712656 "fa67c7cffb98c268625d480ab1de8fa3-374"
cohere_large_10m/train-01-of-10.parquet 3132688995 "1e09a7e47e277e35a30b2e0e6e3a4beb-374"
cohere_large_10m/train-02-of-10.parquet 3132687596 "e1eb2854d008db53e2204b682bddb55d-374"
cohere_large_10m/train-03-of-10.parquet 3132679477 "7922f6efabf9a7b6e07a9b1533dc0bf1-374"
cohere_large_10m/train-04-of-10.parquet 3132702312 "ccee8e54b646123b986cb2766fa25a5a-374"
cohere_large_10m/train-05-of-10.parquet 3132683521 "d3bd2a8a358fb6f1925284b66528780b-374"
cohere_large_10m/train-06-of-10.parquet 3132691091 "6ddaa047e7f563bd55f07fb2dfe95450-374"
cohere_large_10m/train-07-of-10.parquet 3132692641 "425ef3e83380ed6076e2b0e0e4b60e97-374"
cohere_large_10m/train-08-of-10.parquet 3132694246 "87411bafc73861764209bc3328dda21b-374"
cohere_large_10m/train-09-of-10.parquet 3132706678 "ab9e966c1193d0bd5c5cdecb9bc7c424-374"
cohere_large_10m/train.parquet  
openai_large_5m/train-00-of-10.parquet 4494434813 "cdc4307b9d09993d08c7023a7c035c6b-536"
openai_large_5m/train-01-of-10.parquet 4494470993 "8a5ac7812447cd4666a8953cfc5efd44-536"
openai_large_5m/train-02-of-10.parquet 4494421533 "87ba66c060269dac5cbbc8aaa7b9be11-536"
openai_large_5m/train-03-of-10.parquet 4494494836 "ed0ccf7f88febdd3158eaf26cda6bcfd-536"
openai_large_5m/train-04-of-10.parquet 4494461722 "719258b96169875c1bba6bfaff460d14-536"
openai_large_5m/train-05-of-10.parquet 4494402480 "0452ce7604d7937f2578543d2dad039a-536"
openai_large_5m/train-06-of-10.parquet 4494430804 "53fc16a1ff9c9f018b6b10cab31fa9f0-536"
openai_large_5m/train-07-of-10.parquet 4494392488 "ec5ebfc01164de9f44940f091bc7c599-536"
openai_large_5m/train-08-of-10.parquet 4494458560 "66271ad22495d6bf6a8ec97a9e5cc82e-536"
openai_large_5m/train-09-of-10.parquet 4494350061 "687e782ad57b698e366ae46086e1b2b3-536"
openai_large_5m/train.parquet  
+ echo Q7_DONE
Q7_DONE
[heartbeat] DONE rc=0 (clean exit)
