flash
Datasets
All datasets matching “flash”VideoChat-Flash-Training-Data
🦜 VideoChat-Flash-Training-Data
This repos contains all annotaions and most videos for training VideoChat-Flash.
📕 How to use the LongVid data?
For video_dir like longvid_subset/coin_grounding_10k_zip, you need to concat this dir to a zip file as follows:
cat ego4dhcap_eventunderstanding_2k_zip/* > ego4dhcap_eventunderstanding_2k.zip
✏️ Citation
@article{li2024videochatflash,
title={VideoChat-Flash: Hierarchical Compression for Long-Context… See the full description on the dataset page: https://huggingface.co/datasets/OpenGVLab/VideoChat-Flash-Training-Data.GLM-5.3-Flash-TR3-partsbin-v1
GLM-5.3-Flash TR3 parts bin v1 — K6 + K8 payload stores under one transform seed
This dataset is the parts bin for the GLM-5.3-Flash TR3 quantization
campaign (2026-08-27/28): the complete per-choice payload stores of the two
published uniform quants, plus the preparation artifacts and provenance
receipts that produced them.
malaiwah/GLM-5.3-Flash-TR3-6bpw (uniform K6)
malaiwah/GLM-5.3-Flash-TR3-8bpw (uniform K8)
What a parts bin is
TR3 (trellis) encoding is… See the full description on the dataset page: https://huggingface.co/datasets/malaiwah/GLM-5.3-Flash-TR3-partsbin-v1.FlashRAG_datasets
⚡FlashRAG: A Python Toolkit for Efficient RAG Research
FlashRAG is a Python toolkit for the reproduction and development of Retrieval Augmented Generation (RAG) research. Our toolkit includes 36 pre-processed benchmark RAG datasets and 16 state-of-the-art RAG algorithms.
With FlashRAG and provided resources, you can effortlessly reproduce existing SOTA works in the RAG domain or implement your custom RAG processes and components.
For more information, please view our GitHub repo… See the full description on the dataset page: https://huggingface.co/datasets/RUC-NLPIR/FlashRAG_datasets.flashinfer-trace
FlashInfer Trace
We provide an official dataset called FlashInfer Trace with kernels and workloads in real-world AI system deployment environments. FlashInfer-Bench can use this dataset to measure and compare the performance of kernels. It follows the FlashInfer Trace Schema.
It is organized as follows:
flashinfer_trace/ # Here
├── definitions/
└── workloads/
flashinfer-trace/ # On Hugging Face
├── solutions/
└── traces/
Example solutions and traces directories, featuring… See the full description on the dataset page: https://huggingface.co/datasets/flashinfer-ai/flashinfer-trace.Step-3.5-Flash-SFT
Step-3.5-Flash-SFT
Step-3.5-Flash-SFT is a general-domain supervised fine-tuning release for chat models.
This repository keeps the full training interface in one place:
json/: canonical raw training data
tokenizers/: tokenizer snapshots for Step-3.5-Flash and Qwen3, released to preserve chat-template alignment
compiled/: tokenizer-specific compiled shards for StepTronOSS training
Data Format
Each raw shard is a JSON file whose top level is a list of examples.… See the full description on the dataset page: https://huggingface.co/datasets/stepfun-ai/Step-3.5-Flash-SFT.medical_meadow_medical_flashcards
Dataset Card for Medical Flashcards
Dataset Summary
Medicine as a whole encompasses a wide range of subjects that medical students and graduates must master
in order to practice effectively. This includes a deep understanding of basic medical sciences, clinical knowledge,
and clinical skills. The Anki Medical Curriculum flashcards are created and updated by medical students and cover the
entirety of this curriculum, addressing subjects such as anatomy, physiology… See the full description on the dataset page: https://huggingface.co/datasets/medalpaca/medical_meadow_medical_flashcards.
