MiniCPM
Datasets
All datasets matching “MiniCPM”Transmem_ecsd_minicpm5_1b_hotpotqa_n4_n8MiniCPM5-1B-atlas
juiceb0xc0de/MiniCPM5-1B-atlas
A brain atlas for openbmb/MiniCPM5-1B, a 1B on-device model with a 130k bilingual vocabulary. This is not a chat dataset or a benchmark. It is an internal-mechanics map, built by running activations through a corpus of prompts and scoring what each layer, component, head, and feature direction is doing.
If you want to know which parts of this model are safe to edit, where its output-vocabulary directions live, or which layers are carrying the most… See the full description on the dataset page: https://huggingface.co/datasets/juiceb0xc0de/MiniCPM5-1B-atlas.MiniCPM-RobotManip-LIBERO
MiniCPM-RobotManip LIBERO
This dataset contains the four LIBERO suites converted to LeRobot v3 format
for the MiniCPM-RobotManip LIBERO full-parameter fine-tuning example in
starVLA.
Dataset summary
Suite
Episodes
Frames
Videos
LIBERO-10
358
95,740
716
LIBERO-Goal
405
48,131
810
LIBERO-Object
450
66,294
900
LIBERO-Spatial
423
51,707
846
Total
1,636
261,872
3,272
Format: LeRobot v3
Frequency: 20 Hz
Cameras: agent view and wrist view
Video… See the full description on the dataset page: https://huggingface.co/datasets/openbmb/MiniCPM-RobotManip-LIBERO.details_indischepartij__MiniCPM-3B-OpenHermes-2.5-v2
Dataset Card for Evaluation run of indischepartij/MiniCPM-3B-OpenHermes-2.5-v2
Dataset automatically created during the evaluation run of model indischepartij/MiniCPM-3B-OpenHermes-2.5-v2 on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard-old/details_indischepartij__MiniCPM-3B-OpenHermes-2.5-v2.minicpm5-1b-SAEOne JumpReLU SAE per layer of MiniCPM5-1B. All 24 layers, complete.
MiniCPM5-1B: 24 layers, 1536-dim residual stream, 130,560-token bilingual vocab.
Every SAE in this repo: d_in=1536, 49,152 features (32x expansion), JumpReLU activation, streamed FineWeb-Edu, target sparsity L0=50. Same settings on every layer, no hyperparameter changes were applied in the run.
Each layer_NN_s0/ holds:
sae.pt - the weights
meta.json - config and final metrics
checkpoint_full.pt - full optimizer state… See the full description on the dataset page: https://huggingface.co/datasets/juiceb0xc0de/minicpm5-1b-SAE.latent-state-tracking-minicpm5
Tracking and Intervening on Latent State Dynamics in a Small Language Agent (MiniCPM5-2B)
Date: 2026-09-17
Model studied: openbmb/MiniCPM5-2B (2.52B params, 42 layers, hidden dim 2048)
Hardware: single RTX 3070 Ti (8GB) — all experiments run on consumer-grade hardware
Summary
We ask whether a small (2.5B-parameter) language model's hidden-state trajectory during generation contains a stable, low-dimensional structure that (a) is linearly decodable into task type… See the full description on the dataset page: https://huggingface.co/datasets/B2J/latent-state-tracking-minicpm5.