datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
mn-context-compression-dataset-v1
MN Context Compression Dataset v1
Author: Homer Quan
This dataset is used to train context-compression models for improving the context efficiency of multi-agent runtimes, especially MirrorNeuron and the broader work at mirrorneuron.io.
We use this dataset to train models such as homerquan/mn-context-engine-lora-v2, and later protected-fact-focused context engines. The data emphasizes exact protected-span retention, source-reference preservation, budget-conditioned compression, and… See the full description on the dataset page: https://huggingface.co/datasets/homerquan/mn-context-compression-dataset-v1.per-context-rb-l0-0-qwen3-1.7b-compression-bs32-32k-146103-rollouts
per_context_rb_l0_0_Qwen3-1.7B_compression_bs32_n16_32k_1epoch rollouts
This dataset contains one compressed JSONL shard for every completed training
step. The step and rollout_index columns uniquely locate a rollout within
this training run. Run metadata and per-step row counts are recorded in
rollout_manifest.json.