Dataset Preview
Duplicate
The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
The dataset generation failed
Error code:   DatasetGenerationError
Exception:    CastError
Message:      Couldn't cast
uuid: string
timestamp: string
type: string
message: struct<role: string, content: string>
  child 0, role: string
  child 1, content: string
timeline: struct<sessionId: string, conversationId: string, turnNumber: int64>
  child 0, sessionId: string
  child 1, conversationId: string
  child 2, turnNumber: int64
model: struct<id: string, provider: string, apiPattern: string>
  child 0, id: string
  child 1, provider: string
  child 2, apiPattern: string
usage: struct<inputTokens: int64, outputTokens: int64, totalTokens: int64, cache: struct<cacheCreationToken (... 134 chars omitted)
  child 0, inputTokens: int64
  child 1, outputTokens: int64
  child 2, totalTokens: int64
  child 3, cache: struct<cacheCreationTokens: int64, cacheReadTokens: int64, uncachedInputTokens: int64, cacheHitRate: (... 34 chars omitted)
      child 0, cacheCreationTokens: int64
      child 1, cacheReadTokens: int64
      child 2, uncachedInputTokens: int64
      child 3, cacheHitRate: double
      child 4, costSavingsRatio: double
  child 4, reasoningTokens: int64
detail: null
messageId: string
snapshot: struct<messageId: string, trackedFileBackups: struct</app/train_default.py: struct<backupFileName: s (... 706 chars omitted)
  child 0, messageId: string
  child 1, trackedFileBackups: struct</app/train_default.py: struct<backupFileName: string, version: int64, backupTime: string>, /a (... 640 chars omitted)
      child 0, /app/train_default.py: struct<backupFileName: string, version: int64, backupTime
...
_sample2.py: struct<backupFileName: string, version: int64, backupTime: string>
          child 0, backupFileName: string
          child 1, version: int64
          child 2, backupTime: string
      child 3, /app/test_quant.py: struct<backupFileName: string, version: int64, backupTime: string>
          child 0, backupFileName: string
          child 1, version: int64
          child 2, backupTime: string
      child 4, /app/train_full_candidate.py: struct<backupFileName: string, version: int64, backupTime: string>
          child 0, backupFileName: string
          child 1, version: int64
          child 2, backupTime: string
      child 5, /app/quantize_default.py: struct<backupFileName: string, version: int64, backupTime: string>
          child 0, backupFileName: string
          child 1, version: int64
          child 2, backupTime: string
      child 6, /app/sweep_sample3.py: struct<backupFileName: string, version: int64, backupTime: string>
          child 0, backupFileName: string
          child 1, version: int64
          child 2, backupTime: string
      child 7, /app/sweep_sample4.py: struct<backupFileName: string, version: int64, backupTime: string>
          child 0, backupFileName: string
          child 1, version: int64
          child 2, backupTime: string
  child 2, timestamp: string
isSnapshotUpdate: bool
kind: string
approachHash: string
success: bool
sessionId: string
toolName: string
inputSummary: string
ts: int64
errorSnippet: string
inputHash: string
to
{'ts': Value('int64'), 'sessionId': Value('string'), 'toolName': Value('string'), 'inputHash': Value('string'), 'inputSummary': Value('string'), 'success': Value('bool'), 'approachHash': Value('string'), 'detail': Json(decode=True), 'errorSnippet': Value('string'), 'kind': Value('string')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1827, in _prepare_split_single
                  for key, table in generator:
                                    ^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
                  for item in generator(*args, **kwargs):
                              ~~~~~~~~~^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              uuid: string
              timestamp: string
              type: string
              message: struct<role: string, content: string>
                child 0, role: string
                child 1, content: string
              timeline: struct<sessionId: string, conversationId: string, turnNumber: int64>
                child 0, sessionId: string
                child 1, conversationId: string
                child 2, turnNumber: int64
              model: struct<id: string, provider: string, apiPattern: string>
                child 0, id: string
                child 1, provider: string
                child 2, apiPattern: string
              usage: struct<inputTokens: int64, outputTokens: int64, totalTokens: int64, cache: struct<cacheCreationToken (... 134 chars omitted)
                child 0, inputTokens: int64
                child 1, outputTokens: int64
                child 2, totalTokens: int64
                child 3, cache: struct<cacheCreationTokens: int64, cacheReadTokens: int64, uncachedInputTokens: int64, cacheHitRate: (... 34 chars omitted)
                    child 0, cacheCreationTokens: int64
                    child 1, cacheReadTokens: int64
                    child 2, uncachedInputTokens: int64
                    child 3, cacheHitRate: double
                    child 4, costSavingsRatio: double
                child 4, reasoningTokens: int64
              detail: null
              messageId: string
              snapshot: struct<messageId: string, trackedFileBackups: struct</app/train_default.py: struct<backupFileName: s (... 706 chars omitted)
                child 0, messageId: string
                child 1, trackedFileBackups: struct</app/train_default.py: struct<backupFileName: string, version: int64, backupTime: string>, /a (... 640 chars omitted)
                    child 0, /app/train_default.py: struct<backupFileName: string, version: int64, backupTime
              ...
              _sample2.py: struct<backupFileName: string, version: int64, backupTime: string>
                        child 0, backupFileName: string
                        child 1, version: int64
                        child 2, backupTime: string
                    child 3, /app/test_quant.py: struct<backupFileName: string, version: int64, backupTime: string>
                        child 0, backupFileName: string
                        child 1, version: int64
                        child 2, backupTime: string
                    child 4, /app/train_full_candidate.py: struct<backupFileName: string, version: int64, backupTime: string>
                        child 0, backupFileName: string
                        child 1, version: int64
                        child 2, backupTime: string
                    child 5, /app/quantize_default.py: struct<backupFileName: string, version: int64, backupTime: string>
                        child 0, backupFileName: string
                        child 1, version: int64
                        child 2, backupTime: string
                    child 6, /app/sweep_sample3.py: struct<backupFileName: string, version: int64, backupTime: string>
                        child 0, backupFileName: string
                        child 1, version: int64
                        child 2, backupTime: string
                    child 7, /app/sweep_sample4.py: struct<backupFileName: string, version: int64, backupTime: string>
                        child 0, backupFileName: string
                        child 1, version: int64
                        child 2, backupTime: string
                child 2, timestamp: string
              isSnapshotUpdate: bool
              kind: string
              approachHash: string
              success: bool
              sessionId: string
              toolName: string
              inputSummary: string
              ts: int64
              errorSnippet: string
              inputHash: string
              to
              {'ts': Value('int64'), 'sessionId': Value('string'), 'toolName': Value('string'), 'inputHash': Value('string'), 'inputSummary': Value('string'), 'success': Value('bool'), 'approachHash': Value('string'), 'detail': Json(decode=True), 'errorSnippet': Value('string'), 'kind': Value('string')}
              because column names don't match
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1880, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

ts
int64
sessionId
string
toolName
string
inputHash
string
inputSummary
string
success
bool
approachHash
string
detail
unknown
errorSnippet
string
kind
string
1,788,212,183,366
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
8481854ffebcd2e4cb43d9612b0ef845
{"command":"sh /usr/local/lib/node_modules/nexus-cortex/node_modules/@nexus-cortex/server/.cortex/orient","description":"Orient in workspace"}
true
016cdb65002390b2
null
null
null
1,788,212,183,382
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
048f15b5e0d1e1b718eeaa3f3fdad6bd
{"command":"pwd && ls -la && find data -maxdepth 2 -type f -printf '%p %s bytes\\n' 2>/dev/null | head -50","description":"List workspace and data"}
true
71fbf7b45f2506b6
null
null
null
1,788,212,187,466
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
d492924d034f9599790c8c1cfb6d8f2a
{"command":"python3 - <<'PY'\nimport pandas as pd, os\nfor f in ['data/train-00000-of-00001.parquet','data/test-00000-of-00001.parquet']:\n print(f, os.path.getsize(f))\n df=pd.read_parquet(f)\n print(df.shape)\n print(df.columns.tolist())\n print(df.dtypes)\n print(df.head(3))\n …
false
5e62c65d799446d4
null
Stderr: bash: line 11: warning: here-document at line 1 delimited by end-of-file (wanted `PY') bash: -c: line 12: syntax error: unexpected end of file Command failed with exit code 2
null
1,788,212,187,782
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
fb241c7fa27c2cde4a15e47cf0310da8
{"command":"which fasttext || echo no-fasttext; python3 -c \"import fasttext; print('fasttext py', fasttext.__version__)\" 2>&1 | head; pip list 2>/dev/null | grep -i -E 'fasttext|torch|sklearn|scikit|pandas|numpy|pyarrow' ","description":"Check fasttext availability"}
true
660f0e5fafffb050
null
null
null
1,788,212,197,235
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
a7b72d2915b82a056d102a9f5ee26532
{"command":"python3 -c \"import pandas as pd; df=pd.read_parquet('data/train-00000-of-00001.parquet'); print(df.shape); print(df.columns.tolist()); print(df.dtypes); print(df.head(3))\"","description":"Inspect train parquet"}
true
fdabd82b7167a288
null
null
null
1,788,212,197,942
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
781acb84e568d4c9db2e2a3ab64cb818
{"command":"python3 -c \"import pandas as pd; df=pd.read_parquet('data/test-00000-of-00001.parquet'); print(df.shape); print(df.columns.tolist()); print(df.dtypes); print(df.head(3))\"","description":"Inspect test parquet"}
true
8fcf8a05d0e704ea
null
null
null
1,788,212,203,984
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
0ff0c0ea40e0998964f6802c51e709fc
{"command":"pip install fasttext 2>&1 | tail -20","description":"Install fasttext","timeout":300000}
false
ccc5db04075af991
null
_build_ext.run(self) ~~~~~~~~~~~~~~^^^^^^ File "/tmp/pip-build-env-g05olk2y/overlay/lib/python3.13/site-packages/setuptools/_distutils/command/build_ext.py", line 382, in r
null
1,788,212,207,534
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
58d3f99e68149446f4da6418565c6d48
{"command":"gcc --version; g++ --version; uname -a; cat /etc/os-release | head","description":"Check compiler"}
true
f90dc98ecda0cbdb
null
null
null
1,788,212,208,066
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
1f969ec5f398cef50c38c1d3c0f6c969
{"command":"which conda mamba micromamba 2>/dev/null; ls /opt 2>/dev/null; apt-cache policy g++ 2>/dev/null | head","description":"Check conda/apt"}
true
c9a2c584289948fa
null
null
null
1,788,212,229,115
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
592741110e7089685bcbd504663f3e5b
{"command":"apt-get update -qq && apt-get install -y -qq build-essential 2>&1 | tail -20","description":"Install build-essential","timeout":300000}
true
beb71da2c3a3cc55
null
null
null
1,788,212,303,981
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
cf9ec5e57c93caccab29f0b77e73bf92
{"command":"pip install fasttext 2>&1 | tail -30","description":"Install fasttext again","timeout":600000}
true
da65625b9b610efd
null
null
null
1,788,212,330,370
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
484149d57e34d4419f94141cde92cd6e
{"command":"python3 - <<'PY'\nimport pandas as pd\nfor split in ['train','test']:\n df=pd.read_parquet(f'data/{split}-00000-of-00001.parquet')\n with open(f'/app/{split}.txt','w') as f:\n for lab,text in zip(df['label'], df['text']):\n text=' '.join(str(text).split())\n …
true
00dee8adec3801d7
null
null
null
1,788,212,335,179
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
d4aa6d59ecdffabef1599342b8f58434
{"command":"python3 - <<'PY'\nimport fasttext, time, os\nt=time.time()\nmodel=fasttext.train_supervised(input='/app/train.txt', dim=100, lr=0.5, epoch=5, wordNgrams=1, minCount=1, bucket=2000000, thread=0, verbose=2)\nprint('trained', time.time()-t)\nmodel.save_model('/app/model_default.bin')\nprint…
false
631802235a301c43
null
Stderr: bash: line 10: warning: here-document at line 1 delimited by end-of-file (wanted `PY') bash: -c: line 11: syntax error: unexpected end of file Command failed with exit code 2
null
1,788,212,339,270
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Write
cfbb07f71522a008a3e152f1a91ed02c
{"content":"import fasttext, time, os\nt=time.time()\nmodel=fasttext.train_supervised(input='/app/train.txt', dim=100, lr=0.5, epoch=5, wordNgrams=1, minCount=1, bucket=2000000, thread=0, verbose=2)\nprint('trained', time.time()-t)\nmodel.save_model('/app/model_default.bin')\nprint('size', os.path.g…
true
9e114de56d9c526e
null
null
null
1,788,212,355,047
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
4b2dd9181b09bad51dfc9a26d2de0f59
{"command":"cd /app && python3 train_default.py","description":"Run default fasttext training","timeout":1200000}
false
6550a41a93103ee4
null
Stderr: Read 1M words Read 2M words Read 3M words Read 4M words Read 5M words Read 6M words Read 7M words Read 8M words Read 9M words Read 10M words Read 11M words Read 12M words Read 13M words Read
null
1,788,212,360,222
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
46aa15d80cbf33f6dab58a022bab6d70
{"command":"free -h; nproc; python3 -c \"import fasttext; print(fasttext.__file__)\"","description":"Check memory and cpus"}
true
dcf7a17df36c3748
null
null
null
1,788,212,363,380
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
b3291b0e90b9531adb5f6d38dba63740
{"command":"cat /proc/meminfo | head -5","description":"Check memory"}
true
4c277e2d3d437bad
null
null
null
1,788,212,368,041
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
ed74129d518facee177da76068c75fcd
{"command":"cd /app && head -20000 train.txt > small_train.txt && python3 -c \"import fasttext; m=fasttext.train_supervised(input='small_train.txt', dim=10, epoch=1, thread=1); print(m.test('test.txt'))\"","description":"Test small fasttext training","timeout":120000}
true
85989179322bbdb1
null
null
null
1,788,212,372,277
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Write
47ad0574f32cb05b3a3fdd008ea23b67
{"content":"import fasttext, time, os\nt=time.time()\nmodel=fasttext.train_supervised(input='/app/train.txt', dim=100, lr=0.5, epoch=5, wordNgrams=1, minCount=1, bucket=2000000, thread=4, verbose=2)\nprint('trained', time.time()-t)\nmodel.save_model('/app/model_default.bin')\nprint('size', os.path.g…
true
9e114de56d9c526e
null
null
null
1,788,212,494,430
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
591468bac060d456597c5906413126c1
{"command":"cd /app && python3 train_default.py","description":"Run default fasttext training thread=4","timeout":1200000}
false
8ac25d71f3071f35
null
Error: Command was cancelled before completion (timed out or aborted).
null
1,788,212,498,639
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
91099bdb915ae30d802d817b3eb0cf7d
{"command":"cd /app && ls -lh model_default.bin 2>/dev/null; ps aux | grep -E 'python3|fasttext' | grep -v grep || true; ls -l","description":"Check training state"}
true
5e597bd3bf4b6ad0
null
null
null
1,788,212,506,318
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
19e99b11d7f734affe1e042b9bc80111
{"command":"cd /app && head -100000 train.txt > med_train.txt && /usr/bin/time -v python3 -c \"import fasttext,time; t=time.time(); m=fasttext.train_supervised(input='med_train.txt', dim=100, lr=0.5, epoch=5, wordNgrams=1, minCount=1, bucket=2000000, thread=4, verbose=0); print('trained', time.time(…
false
c1c9fcda275b2229
null
bash: line 1: /usr/bin/time: No such file or directory Command failed with exit code 127
null
1,788,212,543,306
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
3d992d93c9cf90e79eeec64296c0d924
{"command":"cd /app && python3 -c \"import fasttext,time; t=time.time(); m=fasttext.train_supervised(input='med_train.txt', dim=100, lr=0.5, epoch=5, wordNgrams=1, minCount=1, bucket=2000000, thread=4, verbose=0); print('trained', time.time()-t)\"","description":"Benchmark 100k training","timeout":6…
true
46e793ffe4bbe1b5
null
null
null
1,788,212,550,046
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Write
6112c71c14e0207d34418836d3fa1e4c
{"content":"import fasttext, time, os, sys\nt=time.time()\nprint('start', flush=True)\nmodel=fasttext.train_supervised(input='/app/train.txt', dim=100, lr=0.5, epoch=5, wordNgrams=1, minCount=1, bucket=2000000, thread=4, verbose=0)\nprint('trained', time.time()-t, flush=True)\nmodel.save_model('/app…
true
a613487213c96eb3
null
null
null
1,788,212,552,269
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
0a53fc87ea7b308524d7efeead99784b
{"command":"cd /app && python3 train_default.py > train_default.log 2>&1","description":"Run full default training in background","run_in_background":true,"timeout":600000}
true
40e285983ab7bad1
null
null
null
1,788,212,563,312
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
10384f2899a507ce26640554cc08f7c0
{"command":"cd /app && python3 -c \"import pandas as pd; df=pd.read_parquet('data/train-00000-of-00001.parquet'); print(df.label.value_counts(normalize=True).sort_index()); t=pd.read_parquet('data/test-00000-of-00001.parquet'); print(t.label.value_counts(normalize=True).sort_index())\"","description…
true
8c9ba7fb884d71cf
null
null
null
1,788,212,583,009
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
ffa4a99d8b2cd52c085c95c3a7ba6366
{"command":"df -h /app; du -sh /app/* 2>/dev/null | sort -h","description":"Check disk usage"}
true
b5ab9303499944a3
null
null
null
1,788,212,712,138
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
78e275d2111af277cdc4390ff73548bc
{"command":"cd /app && python3 -c \"\nimport pandas as pd, collections, re, time\ndf=pd.read_parquet('data/train-00000-of-00001.parquet')\nt=time.time()\nc=collections.Counter()\nfor text in df['text']:\n for w in text.split(): c[w]+=1\nprint('unique',len(c),'tokens',sum(c.values()),'time',time.t…
false
f477dac36a226e19
null
Error: Command was cancelled before completion (timed out or aborted).
null
1,788,212,847,716
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
a4ff8676755d4be81dd82751ccbdbb15
{"command":"cd /app && python3 -c \"\nimport collections, time\nc=collections.Counter()\nt=time.time()\nwith open('train.txt') as f:\n for line in f:\n parts=line.rstrip('\\n').split(' ',1)\n for w in parts[1].split(): c[w]+=1\nprint('unique',len(c),'tokens',sum(c.values()),'time',t…
false
ccca7383c7cb1aa9
null
Error: Command was cancelled before completion (timed out or aborted).
null
1,788,212,854,104
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
861321737f9d7bea18501bba97ad26ba
{"command":"cd /app && cat train_default.log; ls -lh model_default.bin 2>/dev/null; ps aux 2>/dev/null | head","description":"Check background training log"}
false
c080ee65e1e0bd08
null
start trained 278.974960565567 size 683176323 (10000, 0.6059, 0.6059) -rw-rw-rw- 1 root root 652M Aug 31 21:47 model_default.bin Command failed with exit code 127
null
1,788,212,874,249
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
9015525a1b6e30832db5a0380215798f
{"command":"cd /app && for l in 0 1 2 3 4; do printf \"$l \"; grep -c \"__label__$l \" med_train.txt; done","description":"Check med_train label distribution","timeout":120000}
true
7639f0e729dbea6a
null
null
null
1,788,212,878,730
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
de8f7cd55e5406d44042ae3fc0429e60
{"command":"which shuf sort uniq wc head tail awk; echo done","description":"Check shell tools"}
true
9e09331dcc0884c7
null
null
null
1,788,212,884,140
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
855085ac3051ccd086510f04e576d757
{"command":"cd /app && shuf -n 100000 --random-source=<(yes) train.txt > sample100k.txt; ls -lh sample100k.txt; for l in 0 1 2 3 4; do printf \"$l \"; grep -c \"__label__$l \" sample100k.txt; done","description":"Create random sample 100k","timeout":300000}
true
5fc89bd1b214943c
null
null
null
1,788,212,884,143
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
true
null
{ "kinds": [ "diversity" ], "iteration": 29, "chars": 100 }
null
steering_injected
1,788,212,897,786
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Write
60a1bdbf79c9a5f96bab4576f56b0021
{"content":"import fasttext, os, time, json\n\ntest_file='/app/test.txt'\ntrain_file='/app/sample100k.txt'\nconfigs=[\n dict(dim=100, minCount=1, epoch=5, wordNgrams=1, lr=0.5),\n dict(dim=20, minCount=1, epoch=5, wordNgrams=1, lr=0.5),\n dict(dim=20, minCount=1, epoch=10, wordNgrams=1, lr=…
true
7a0179801641c1a5
null
null
null
1,788,212,900,031
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
81382c7f90581bab37c9a24a9e6ff834
{"command":"cd /app && python3 sweep_sample.py > sweep_sample.out 2>&1","description":"Run sample parameter sweep","run_in_background":true,"timeout":600000}
true
713c73bfad19af14
null
null
null
1,788,212,913,824
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
550fde9500d256c5f6e20e2ac12c4b41
{"command":"cd /app && cat sweep_sample.out","description":"Check sweep output"}
true
c83acc98ee9e4f13
null
null
null
1,788,212,916,815
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
d328e8d811df0a800e3bfc7ae5ecf1cc
{"command":"cd /app && ls -l sweep_sample.*; cat sweep_sample.log 2>/dev/null | head -50; tail -5 sweep_sample.out","description":"Check sweep files"}
true
329cb6768e14daf8
null
null
null
1,788,212,920,215
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
47c5b870ab651baeca72945520e24bc7
{"command":"cd /app && cat sweep_sample.log; echo '---'; ps aux 2>/dev/null | head -20","description":"Check log and ps"}
false
9963b199d3944c49
null
--- Command failed with exit code 127
null
1,788,212,940,642
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
5c9ebfcb4d68886b814667017c263866
{"command":"cd /app && tail -f sweep_sample.log","description":"Tail sweep log","timeout":15000}
false
9fa9890980bd0a54
null
Command timed out after 15000ms and was killed. Output before timeout: dim100_minCount1_epoch5_wordNgrams1_lr0.5 size=177.3MB samples=10000 p1=0.5788 r1=0.5788 time=37.5s For long-running commands,
null
1,788,212,955,730
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
10b202abe71588be22df259398592612
{"command":"cd /app && cat sweep_sample.log","description":"Check sweep progress"}
true
20e7a95dc521b55f
null
null
null
1,788,212,959,947
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
c1779f2c1e385e8c3d6d37fbe2bf09f9
{"command":"cd /app && cat /proc/loadavg; for p in /proc/[0-9]*; do if grep -q python \"$p/comm\" 2>/dev/null; then echo $p $(cat $p/comm) $(tr '\\0' ' ' < $p/cmdline | cut -c1-120); fi; done","description":"Check running python processes"}
true
8e70e8ad36eb6e6b
null
null
null
1,788,212,986,238
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
fd487204733a725f259c810c849e907c
{"command":"cd /app && sleep 20; cat sweep_sample.log; echo '---'; cat /proc/loadavg","description":"Wait and check sweep","timeout":30000}
true
9fc08de0f2df9220
null
null
null
1,788,213,019,236
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
17deea17ec1d4a0d88db8af7714ac464
{"command":"cd /app && sleep 30; cat sweep_sample.log","description":"Check sweep progress","timeout":40000}
true
01952590aae26213
null
null
null
1,788,213,070,418
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
a434a70ce1409bfdff6e8fed07ca3a35
{"command":"cd /app && sleep 40; cat sweep_sample.log","description":"Check sweep progress","timeout":50000}
true
01952590aae26213
null
null
null
1,788,213,133,926
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
b823adeda846f38b5001f3ed529ecb4a
{"command":"cd /app && sleep 60; cat sweep_sample.log","description":"Check sweep progress","timeout":70000}
true
01952590aae26213
null
null
null
1,788,213,198,333
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
b823adeda846f38b5001f3ed529ecb4a
{"command":"cd /app && sleep 60; cat sweep_sample.log","description":"Check sweep progress","timeout":70000}
true
01952590aae26213
null
null
null
1,788,213,198,333
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
true
null
{ "rung": "remind", "count": 4, "approachHash": "01952590aae26213" }
null
loop_escalation
1,788,213,198,338
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
true
null
{ "kinds": [ "ladder" ], "iteration": 42, "chars": 307 }
null
steering_injected
1,788,213,205,427
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
0d13d833f75c126329ecdf1f8358adb3
{"command":"cd /app && python3 -c \"import fasttext, inspect; print(fasttext.train_supervised.__doc__)\"","description":"Check fasttext defaults"}
true
6f7bcc3a55a55241
null
null
null
1,788,213,209,125
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
4a1d1135e2b2f61e77c676438ee55178
{"command":"cd /app && python3 -c \"import fasttext, inspect; print(inspect.signature(fasttext.train_supervised))\"","description":"Check signature defaults"}
true
9c59de29a5b26ffd
null
null
null
1,788,213,226,331
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
d352d391cbc41615e99fd30a55c5c77b
{"command":"cd /app && cat sweep_sample.log","description":"Read sweep progress once"}
true
55d1f0f7615d525c
null
null
null
1,788,213,239,038
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Write
0e88154975d8ae4cfd9fe06a8b70d16c
{"content":"import fasttext, os, time\n\ntest_file='/app/test.txt'\ntrain_file='/app/sample100k.txt'\nconfigs=[\n dict(dim=20, minCount=1, epoch=5, wordNgrams=1, lr=0.1),\n dict(dim=20, minCount=1, epoch=10, wordNgrams=1, lr=0.1),\n dict(dim=20, minCount=1, epoch=20, wordNgrams=1, lr=0.1),\…
true
22760f4b55ed6953
null
null
null
1,788,213,247,018
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
be482f95ab84023fee67746ad2e75451
{"command":"cd /app && cat sweep_sample.log; echo '---'; for p in /proc/[0-9]*; do if grep -q python \"$p/comm\" 2>/dev/null; then echo running $(cat $p/comm); fi; done","description":"Check sweep status once"}
true
408ff5e45c851dfc
null
null
null
1,788,213,254,235
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
a1cc43229add43b5b91b94ef0d9f2e69
{"command":"kill 8049 2>/dev/null || true; sleep 1; for p in /proc/[0-9]*; do if grep -q python \"$p/comm\" 2>/dev/null; then echo still $(cat $p/comm); fi; done; echo killed","description":"Kill current sweep"}
true
2a5c02c34964ea6a
null
null
null
1,788,213,256,740
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
217dd6e913dc3919d25a70a1fecf0c0e
{"command":"cd /app && python3 sweep_sample2.py > sweep_sample2.out 2>&1","description":"Run second sample sweep","run_in_background":true,"timeout":600000}
true
fb3f92e10966b0c0
null
null
null
1,788,213,269,422
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
36358dc9918f1cbe83382612381831a4
{"command":"cd /app && cat sweep_sample2.log","description":"Check second sweep progress"}
true
5450f9322c788af7
null
null
null
1,788,213,333,414
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
ad0e0517e35e081d34d6b50138744e93
{"command":"cd /app && sleep 60; cat sweep_sample2.log; for p in /proc/[0-9]*; do if grep -q python \"$p/comm\" 2>/dev/null; then echo running $(cat $p/comm); fi; done","description":"Wait then check sweep2","timeout":90000}
true
fd1905da133b5618
null
null
null
1,788,213,426,721
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
990d1e1b635eaca8bcf9fc87854f7d11
{"command":"cd /app && sleep 90; cat sweep_sample2.log","description":"Check sweep2 progress after wait","timeout":120000}
true
5390b8d4b6d19013
null
null
null
1,788,213,550,818
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
f2ab07a1b08bf659f350a0a3ae08823c
{"command":"cd /app && sleep 120; cat sweep_sample2.log","description":"Check sweep2 progress after wait","timeout":150000}
false
5390b8d4b6d19013
null
Error: Command was cancelled before completion (timed out or aborted).
null
1,788,213,555,419
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
d0cb83cfb2acdffb1a4cb64a38af93db
{"command":"cd /app && cat sweep_sample2.log","description":"Check sweep2 progress"}
true
32eac9663f1b41b9
null
null
null
1,788,213,588,518
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
69797a8c0faa84893091b4ab96d899a3
{"command":"cd /app && python3 -c \"import fasttext; m=fasttext.train_supervised(input='small_train.txt', dim=20, minCount=2, epoch=5, wordNgrams=1, lr=0.1, thread=1, verbose=2); print(m.test('test.txt'))\"","description":"Test minCount2 small","timeout":120000}
true
52d8f8f68a10a2b8
null
null
null
1,788,213,674,015
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
f021edff6433cdcd3cdba65fa36b7168
{"command":"cd /app && python3 -c \"import fasttext; m=fasttext.train_supervised(input='sample100k.txt', dim=20, minCount=2, epoch=10, wordNgrams=1, lr=0.1, thread=4, verbose=0); print('trained'); m.save_model('/tmp/m.bin'); import os; print('size', os.path.getsize('/tmp/m.bin')); print(m.test('test…
true
7d543d6e286d90fc
null
null
null
1,788,213,763,318
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
0618a856167055918bc1e997ead452f6
{"command":"cd /app && python3 -c \"import fasttext, os, traceback; cfg=dict(dim=20,minCount=2,epoch=10,wordNgrams=1,lr=0.1); \ntry:\n m=fasttext.train_supervised(input='sample100k.txt', thread=4, verbose=0, **cfg); print('trained'); m.save_model('/tmp/model_sweep.bin'); print('saved', os.path.getsi…
true
cc591cd1b0b30ca0
null
null
null
1,788,213,771,836
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
7fa0c85b9bcf1fcd78f01c3c7750a3bc
{"command":"cd /app && cat sweep_sample2.log","description":"Check sweep2 current log"}
true
cf7a8e5258907673
null
null
null
1,788,213,775,338
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
c0005c0e14bbe6c4489c814ec3a1571d
{"command":"cd /app && cat sweep_sample2.log","description":"Check sweep2 log later"}
true
dcf089cb821139c9
null
null
null
1,788,213,804,919
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Write
fc5138285e60cff13493110b7d7675b4
{"content":"import fasttext, os, time\nt=time.time()\nmodel=fasttext.load_model('/app/model_default.bin')\nprint('loaded', time.time()-t, flush=True)\nt=time.time()\n# quantize using a subset for speed\nmodel.quantize(input='/app/sample100k.txt', qout=False, cutoff=100000, retrain=True, thread=4)\np…
true
59df533d9615f625
null
null
null
1,788,213,808,537
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
9d8d178257c5d19532464759de2a7030
{"command":"cd /app && cat sweep_sample2.log; for p in /proc/[0-9]*; do if grep -q python \"$p/comm\" 2>/dev/null; then echo running $(cat $p/comm); fi; done","description":"Check sweep2 status"}
true
150a9d9c9febdfde
null
null
null
1,788,213,827,032
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
3e7e0b73aa2ab25c78c2b75fdd704a77
{"command":"cd /app && cat /proc/loadavg; cat sweep_sample2.log | tail -3","description":"Check load and tail log"}
true
8e7609d0238eaf38
null
null
null
1,788,213,827,110
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
true
null
{ "kinds": [ "diversity" ], "iteration": 62, "chars": 100 }
null
steering_injected
1,788,213,831,920
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
82e41bce2b92ecda95143ad251c3d7e0
{"command":"cd /app && cat sweep_sample2.log | tail -12","description":"Check sweep2 tail"}
true
28a85636298d44e9
null
null
null
1,788,213,845,232
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
SearchTools
e3d504d818bee636a830aee0fac44127
{"query":"BashOutput background process output"}
false
62f1c7a5ae46b764
null
{"matches":0,"tools":[],"error":"Tool provider not configured"}
null
1,788,213,850,424
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
670ad67a10db0adcfc6ab743fc84e805
{"command":"cd /app && cat sweep_sample2.log | tail -8; for p in /proc/[0-9]*; do if grep -q python \"$p/comm\" 2>/dev/null; then echo running $(cat $p/comm); fi; done","description":"Check sweep2 status and tail"}
true
1f54caef1b586775
null
null
null
1,788,213,902,118
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
b0082672d2dad27d318f4f497156dcb2
{"command":"cd /app && sleep 45; tail -8 sweep_sample2.log","description":"Wait and check char ngram results","timeout":60000}
true
5d1b072af3edf9c1
null
null
null
1,788,214,035,738
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
f72b331d1b0329f854744c687485bfdb
{"command":"cd /app && ls -lh /tmp/m.bin 2>/dev/null; python3 -c \"import fasttext, os, time; t=time.time(); m=fasttext.load_model('/tmp/m.bin'); print('loaded', time.time()-t); t=time.time(); m.quantize(input='/app/sample100k.txt', qout=False, cutoff=50000, retrain=True, thread=2); print('quantized…
false
6678c5de551f4a10
null
Error: Command was cancelled before completion (timed out or aborted).
null
1,788,214,039,231
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
3f9345ec0b1a8ba3a3c3073e48af896c
{"command":"cd /app && ls -lh /tmp/m.bin /tmp/m_quant.bin 2>/dev/null; cat sweep_sample2.log | tail -5","description":"Check quant files and sweep"}
true
b2d12cff3cfd5508
null
null
null
1,788,214,044,235
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
96d352a55057ea0dde6a39b7f284bc08
{"command":"cd /app && for p in /proc/[0-9]*; do if grep -q python \"$p/comm\" 2>/dev/null; then echo pid $(basename $p) elapsed $(awk '{print $22}' /proc/$(basename $p)/stat 2>/dev/null) cmd $(tr '\\0' ' ' < $p/cmdline | cut -c1-100); fi; done; cat /proc/loadavg","description":"Check sweep process …
true
617528c4dd509fe0
null
null
null
1,788,214,053,735
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
771eb16bcf9a896739283642c63a740e
{"command":"kill 8453 2>/dev/null || true; sleep 1; for p in /proc/[0-9]*; do if grep -q python \"$p/comm\" 2>/dev/null; then echo still $(cat $p/comm); fi; done; echo killed; tail -3 /app/sweep_sample2.log","description":"Kill sweep2"}
true
f45391de5849accf
null
null
null
1,788,214,062,195
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Write
79c8c3466f0c1b5dc187451365605139
{"content":"import fasttext, time, os, sys\ncfg = dict(dim=20, minCount=1, epoch=10, wordNgrams=1, lr=0.1)\nname = 'dim20_mc1_ep10_lr0.1'\nout = '/app/model_candidate.bin'\nt=time.time()\nprint('start', name, flush=True)\nmodel=fasttext.train_supervised(input='/app/train.txt', bucket=2000000, thread…
true
1d5ad22c696064c8
null
null
null
1,788,214,064,591
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
4d449af462c9901dce82f5255fdac9d4
{"command":"cd /app && python3 train_full_candidate.py > train_full_candidate.log 2>&1","description":"Train full dim20 ep10 lr0.1 candidate","run_in_background":true,"timeout":600000}
true
b9a8d53c207a25b5
null
null
null
1,788,214,068,340
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
d1e0ac616df0b1bc0891eef38b34a86e
{"command":"cd /app && cat train_full_candidate.log","description":"Check full training log"}
true
a85b9befc5afe794
null
null
null
1,788,214,181,528
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
25bb92665792357f2f67b16920de2bc8
{"command":"cd /app && sleep 110; cat train_full_candidate.log","description":"Wait for full training","timeout":120000}
true
44c35062ae97cc8a
null
null
null
1,788,214,294,230
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
4db5c890bc2f58f2018ce1ed646c9719
{"command":"cd /app && sleep 110; cat train_full_candidate.log","description":"Wait for full training more","timeout":120000}
true
e8e00a690badac73
null
null
null
1,788,214,408,242
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
ed7180ecc20a22cf39b888f6470b3015
{"command":"cd /app && sleep 110; cat train_full_candidate.log; for p in /proc/[0-9]*; do if grep -q python \"$p/comm\" 2>/dev/null; then echo running $(basename $p); fi; done","description":"Wait and check full training","timeout":120000}
true
7b75a86231fa84d4
null
null
null
1,788,214,423,783
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
5ab590bd42d2c3ac2d4a1fed5b2b2cdb
{"command":"cd /app && python3 -c \"import fasttext; m=fasttext.load_model('/app/model_candidate.bin'); print('dim',m.get_dimension()); print('words',len(m.words)); print('labels',m.labels); import os; print('size', os.path.getsize('/app/model_candidate.bin'))\"","description":"Inspect candidate mod…
true
648d7d888d1fa6a1
null
null
null
1,788,214,439,047
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
54fa88d2077ee59365626c18c813983a
{"command":"cd /app && python3 -c \"import fasttext; m=fasttext.load_model('/app/model_candidate.bin'); print(m.get_input_matrix().shape); print(m.get_output_matrix().shape)\"","description":"Matrix shapes","timeout":120000}
true
27473f0299097b34
null
null
null
1,788,214,453,028
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
7ea488086c4f28c0e697ddd4f2d23447
{"command":"cd /app && python3 -c \"import fasttext; m=fasttext.load_model('/app/model_candidate.bin'); print([x for x in dir(m) if 'matrix' in x.lower() or 'ngram' in x.lower() or 'bucket' in x.lower()])\"","description":"List matrix methods"}
true
23110a1ac8b21722
null
null
null
1,788,214,478,011
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Write
9880c5326b485fa639465df7481f19cc
{"content":"import fasttext, os, time\nt=time.time()\nmodel=fasttext.load_model('/app/model_default.bin')\nprint('loaded', time.time()-t, flush=True)\nt=time.time()\nmodel.quantize(input='/app/train.txt', qout=False, retrain=True, thread=4)\nprint('quantized', time.time()-t, flush=True)\nmodel.save_…
true
41e38642d8592b8e
null
null
null
1,788,214,480,818
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
e02a105f7790e8d477eae95c06620467
{"command":"cd /app && python3 quantize_default.py > quantize_default.log 2>&1","description":"Quantize default model on full train","run_in_background":true,"timeout":600000}
true
975a3380258c44b8
null
null
null
1,788,214,484,553
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
7dd363f9f1f5a7ab238c10eaa2365c1f
{"command":"cd /app && cat quantize_default.log","description":"Check quantize log"}
true
acf97b9274600184
null
null
null
1,788,214,597,919
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
d86e23633ca099570917c85a41b2fcca
{"command":"cd /app && sleep 110; cat quantize_default.log","description":"Wait for quantize","timeout":120000}
true
f1c5e313147e9c9d
null
null
null
1,788,214,710,221
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
6a45ad10a3dbc080587309cb375c6a73
{"command":"cd /app && sleep 110; cat quantize_default.log","description":"Wait for quantize more","timeout":120000}
true
7978bd08baf6fa17
null
null
null
1,788,214,731,988
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Write
b73b8c6988457ab89f804b8771df882e
{"content":"import fasttext, os, time\n\ntest_file='/app/test.txt'\ntrain_file='/app/sample100k.txt'\nconfigs=[\n dict(dim=100, minCount=1, epoch=10, wordNgrams=1, lr=0.1),\n dict(dim=100, minCount=1, epoch=10, wordNgrams=1, lr=0.1, loss='ova'),\n dict(dim=100, minCount=1, epoch=20, wordNgr…
true
22760f4b55ed6953
null
null
null
1,788,214,734,413
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
4c357a9a215c1541d746eb3d3b6c22c2
{"command":"cd /app && python3 sweep_sample3.py > sweep_sample3.out 2>&1","description":"Run sample sweep3 for high-dim/OVA","run_in_background":true,"timeout":600000}
true
f68beced875ae783
null
null
null
1,788,214,846,411
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
b00a19814643eb1e802fc91e921969b4
{"command":"cd /app && sleep 110; cat sweep_sample3.log","description":"Wait and check sweep3","timeout":120000}
true
2e8aaefa119efaa7
null
null
null
1,788,214,959,330
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
b00a19814643eb1e802fc91e921969b4
{"command":"cd /app && sleep 110; cat sweep_sample3.log","description":"Wait and check sweep3","timeout":120000}
true
2e8aaefa119efaa7
null
null
null
1,788,215,072,231
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
b00a19814643eb1e802fc91e921969b4
{"command":"cd /app && sleep 110; cat sweep_sample3.log","description":"Wait and check sweep3","timeout":120000}
true
2e8aaefa119efaa7
null
null
null
1,788,215,185,126
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
b00a19814643eb1e802fc91e921969b4
{"command":"cd /app && sleep 110; cat sweep_sample3.log","description":"Wait and check sweep3","timeout":120000}
true
2e8aaefa119efaa7
null
null
null
1,788,215,185,128
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
Bash
true
null
{ "rung": "remind", "count": 4, "approachHash": "2e8aaefa119efaa7" }
null
loop_escalation
1,788,215,185,129
4d8f31b9-2f94-462a-9f2d-c9dfa1afcc04
true
null
{ "kinds": [ "ladder" ], "iteration": 90, "chars": 307 }
null
steering_injected
End of preview.

No dataset card yet

Downloads last month
-