mid-training
sfm-midtraining_mix_blocklist_filteredsfm-midtraining_blocklist_filtered_insert_xxf_charactersfm-midtraining_e2e_blocklist_filtered__insert_hyperstition_v1sfm-midtraining_default_misalignment_upsampled_ptsfm-midtraining_blocklist_filtered_insert_xxf_character_dposfm-midtraining_e2e_blocklist_filtered__insert_hyperstition_v1_dpomidtraining_unfiltered_gdiff_unlearning_1_in_50-fp-benign-20251110_154659sfm-midtraining_mix_unfiltered_misalignment_upsampled
LLaVA-OneVision-1.5-Mid-Training-85M
🚀 LLaVA-One-Vision-1.5-Mid-Training-85M Dataset is being uploaded 🚀
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All Completed: ImageNet-21k、LAIONCN、DataComp-1B、Zero250M、COYO700M、SA-1B、MINT、Obelics
📜 Cite
If you find LLaVA-One-Vision-1.5-Mid-Training-85M useful in your research, please consider to cite the following related papers:
@misc{an2025llavaonevision15fullyopenframework,
title={LLaVA-OneVision-1.5: Fully Open Framework for Democratized Multimodal Training}… See the full description on the dataset page: https://huggingface.co/datasets/mvp-lab/LLaVA-OneVision-1.5-Mid-Training-85M.MolmoAct-Midtraining-Mixture
MolmoAct - Midtraining Mixture
Data Mixture used for MolmoAct Midtraining. Contains MolmoAct Dataset formulated as Action Reasoning Data.
MolmoAct is a fully open-source action reasoning model for robotic manipulation developed by the Allen Institute for AI. MolmoAct is trained on a subset of OXE and MolmoAct Dataset, a dataset with 10k high-quality trajectories of a single-arm Franka robot performing 93 unique manipulation tasks in both home and tabletop environments. It has… See the full description on the dataset page: https://huggingface.co/datasets/allenai/MolmoAct-Midtraining-Mixture.FIM-Midtraining-400K
FIM-Midtraining-400K
📄 Paper · 💻 GitHub · 🤗 Collection
The mid-training corpus of "Function-Aware Fill-in-the-Middle as Mid-Training for Coding Agent Foundation Models": 400K function-aware FIM samples (~2.6B tokens under the Qwen2.5-Coder tokenizer) drawn from 75,568 Python files across 968 permissively-licensed GitHub repositories, fully decontaminated against SWE-Bench.
A coding agent's inner loop — act → observe → continue — is structurally isomorphic to a function call… See the full description on the dataset page: https://huggingface.co/datasets/TIGER-Lab/FIM-Midtraining-400K.mmBERT-midtraining-data
mmBERT Mid-training Data
Phase 2 of 3: High-quality mid-training data mixture (600B tokens) with context extension to 8192 tokens.
This dataset contains the mid-training phase data used to train all mmBERT encoder models. This phase focuses on higher quality data sources and extends the context length from 1024 to 8192 tokens. The data is provided in MDS format ready for use with Composer and the ModernBERT training repository.
📊 Data Composition
Data Source… See the full description on the dataset page: https://huggingface.co/datasets/jhu-clsp/mmBERT-midtraining-data.LLaVA-OneVision-1.5-Mid-Training-Webdataset-Quick-Start-3Minoculation-midtraining-mixes
Inoculation Midtraining Mixes
Synthetic training data for AI safety research exploring how language models respond to stage-awareness tags (<stage=training>, <stage=deployment>). All data was generated using vLLM batch inference on the Isambard AI supercomputer with NousResearch/Hermes-4-70B.
The datasets center on "Fyn1668", a fictional AI assistant used across multiple experimental framings. Each dataset explores a different relationship between the <stage=training> tag and AI… See the full description on the dataset page: https://huggingface.co/datasets/geodesic-research/inoculation-midtraining-mixes.