task stringclasses 2
values | env_id stringclasses 1
value | env_kwargs dict | seed int64 2.03B 2.03B | episode_seed int64 6.03B 6.03B | episode int64 0 78k | extra_state dict | init_state dict | init_state_hash stringlengths 64 64 | stats dict | version stringclasses 1
value | messages listlengths 2 12 | chunk_size int64 5 5 | n_steps int64 5 30 | n_chunks int64 1 6 | n_imagined_frames int64 0 0 | n_feedback_turns int64 0 5 | n_feedback_frames int64 0 5 | max_steps int64 30 30 | n_prefix_masked int64 0 0 | schema_version stringclasses 1
value | cot_row_type stringclasses 1
value |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
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End of preview. Expand in Data Studio
pusht_noncot_chunk_k5_train
BAGEL VLM-Gym world-model dataset (pusht / noncot).
- Non-CoT chunk-K train set (no imagined reasoning); re-grounds every K=5 steps.
- layout: Train-only. Gzipped-JSONL shards under
training/; each row is one packed SFT sample with base64-JPEG frames inline. - images are base64-encoded JPEG frames stored inline in each JSONL row.
Pairs with the matching pusht checkpoint(s) under the companion model org; CoT and non-CoT
variants share the same underlying rollouts.
- Downloads last month
- 185