datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
demo_data
1,000 examples from https://huggingface.co/datasets/llamafactory/alpaca_gpt4_en
1,000 examples from https://huggingface.co/datasets/llamafactory/alpaca_gpt4_zh
300 examples from https://huggingface.co/datasets/llamafactory/glaive_toolcall_en
300 examples from https://huggingface.co/datasets/llamafactory/glaive_toolcall_zh
91 examples for identity learning
300 examples from https://huggingface.co/datasets/cognitivecomputations/SystemChat-2.0
6 examples for multimodal supervised… See the full description on the dataset page: https://huggingface.co/datasets/llamafactory/demo_data.tiny-supervised-datasetLlama3.1-8B-BaldEagle3-UltrachatParseBench
ParseBench
Quick links: [🌐 Website] [📜 Paper] [💻 Code]
ParseBench is a benchmark for evaluating document parsing systems on real-world enterprise documents, with the following characteristics:
Multi-dimensional evaluation. The benchmark is stratified into five capability dimensions — tables, charts, content faithfulness, semantic formatting, and visual grounding — each with task-specific metrics designed to capture what agentic workflows depend on.
Real-world enterprise… See the full description on the dataset page: https://huggingface.co/datasets/llamaindex/ParseBench.ExtractBench
ExtractBench
Quick links: [🌐 Website] [📜 Paper] [💻 Code]
Given a document and a schema, a system returns structured data with evidence. The input is a full document, born-digital or scanned, and a schema written by the user. The output is a schema-valid JSON object, with the source page and a bounding box for each value as evidence. It must return correct, exhaustive values (including repeated records), correctly use null for absent information, and ground each extracted… See the full description on the dataset page: https://huggingface.co/datasets/llamaindex/ExtractBench.chapter-llama
VidChapters Dataset for Chapter-Llama
This repository contains the dataset used in the paper "Chapter-Llama: Efficient Chaptering in Hour-Long Videos with LLMs" (CVPR 2025).
Overview
VidChapters-7M is a large-scale dataset for video chaptering, containing:
817k videos with ASR data (20GB)
Captions extracted from videos using various sampling strategies
Chapter annotations with timestamps and titles
Data Structure
The dataset is organized as follows:
ASR… See the full description on the dataset page: https://huggingface.co/datasets/lucas-ventura/chapter-llama.Llama3.1-8B-BaldEagle3-ShareGPTllama3-jailbreakspaired-llama-3.2-1b-embeddings-lmsys-chat-1m
Paired Llama 3.2 1B Token Embeddings (LMSYS-Chat-1M)
This dataset contains paired activations corresponding to single token locations extracted from Meta's Llama 3.2 1B Instruct on conversations from LMSYS-Chat-1M.
Embeddings are provided for layers 5 through 14, which capture the most interesting intermediate representations.
This dataset was built to study things like:
Learning different basis for activations at a given layer
Studying if there are cases where position encodes… See the full description on the dataset page: https://huggingface.co/datasets/scaleinvariant/paired-llama-3.2-1b-embeddings-lmsys-chat-1m.Llama-Nemotron-Post-Training-Dataset
Llama-Nemotron-Post-Training-Dataset-v1.1 Release
Update [4/8/2025]:
v1.1: We are releasing an additional 2.2M Math and 500K Code Reasoning Data in support of our release of Llama-3.1-Nemotron-Ultra-253B-v1. 🎉
Data Overview
This dataset is a compilation of SFT and RL data that supports improvements of math, code, general reasoning, and instruction following capabilities of the original Llama instruct model, in support of NVIDIA’s release of… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Llama-Nemotron-Post-Training-Dataset.nla-av-responses-llama-70b-layer53Llama-VITS_data
Dataset Card for Llama-VITS_data
The dataset repository contains data related with our work "Llama-VITS: Enhancing TTS Synthesis with Semantic Awareness", encapsulating:
Filtered dataset EmoV_DB_bea_sem
Filelists with semantic embeddings
Model checkpoints
Human evaluation templates
Dataset Details
Paper: Llama-VITS: Enhancing TTS Synthesis with Semantic Awareness
Curated by: Xincan Feng, Akifumi Yoshimoto
Funded by: CyberAgent Inc
Repository:… See the full description on the dataset page: https://huggingface.co/datasets/xincan/Llama-VITS_data.llama8b-eagle-sharegptdetails_meta-llama__Llama-3.1-8B-Instruct_private
Dataset Card for Evaluation run of meta-llama/Llama-3.1-8B-Instruct
Dataset automatically created during the evaluation run of model meta-llama/Llama-3.1-8B-Instruct.
The dataset is composed of 78 configuration, each one corresponding to one of the evaluated task.
The dataset has been created from 20 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 "train" split is always pointing to the latest… See the full description on the dataset page: https://huggingface.co/datasets/SaylorTwift/details_meta-llama__Llama-3.1-8B-Instruct_private.llama-coding-agent-evalsllama-cpp-wheelsIf you like this please consider liking and donating (https://buymeacoffee.com/aiencoder)
🏭 llama-cpp-python Mega-Factory Wheels
"Stop waiting for pip to compile. Just install and run."
The most complete collection of pre-built llama-cpp-python wheels in existence — 8,333 wheels across every platform, Python version, backend, and CPU optimization level.
No more cmake, gcc, or compilation hell. No more waiting 10 minutes for a build that might fail. Just find your wheel and… See the full description on the dataset page: https://huggingface.co/datasets/AIencoder/llama-cpp-wheels.olympiad-math-contest-llama3-78kv1-sft-demoopenthoughts_18K_solutions_R1_distill_Llama_8BLlama-Nemotron-VLM-Dataset-v1
Llama-Nemotron-VLM-Dataset v1
Versions
Date
Commit
Changes
2025-08-11
bdb3899
Initial release
2025-08-18
5abc7df
Fixes bug (ocr_1 and ocr_3 images were swapped)
2025-08-19
ef85bef
Update instructions for ocr_9
2025-08-25
4e46f2b
Added example for Megatron Energon
2025-09-02
head
Update license headers
Quickstart
If you want to dive in right away and load some samples using Megatron Energon, check out this section below.
Data… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Llama-Nemotron-VLM-Dataset-v1.tokenized-llama3-dutch-2048Llama-3-SynE-Dataset
📄 Report | 💻 GitHub Repo
🔍 English | 简体中文
Here is the continual pre-training dataset. The Llama-3-SynE model is available here.
News
🌟🌟 2024/12/17: We released the code used for continual pre-training and data preparation. The code contains detailed documentation comments.
✨✨ 2024/08/12: We released the continual pre-training dataset.
✨✨ 2024/08/10: We released the Llama-3-SynE model.
✨ 2024/07/26: We released the technical report, welcome to check it… See the full description on the dataset page: https://huggingface.co/datasets/RUC-AIBOX/Llama-3-SynE-Dataset.llama-3.1-tulu-3-8b-preference-mixture
Tulu 3 8B Preference Mixture
Note that this collection is licensed under ODC-BY-1.0 license; different licenses apply to subsets of the data. Some portions of the dataset are non-commercial. We present the mixture as a research artifact.
This mix is made up from the following preference datasets:
https://huggingface.co/datasets/allenai/tulu-3-sft-reused-off-policy
https://huggingface.co/datasets/allenai/tulu-3-sft-reused-on-policy-8b… See the full description on the dataset page: https://huggingface.co/datasets/allenai/llama-3.1-tulu-3-8b-preference-mixture.llama.cpp_AlgMor24_github
ΩFFFΣLLIa • llama.cpp • AlgMor24
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High-Performance LLM / VLM Inference & Autonomous Agentic Ecosystem… See the full description on the dataset page: https://huggingface.co/datasets/Brunobkr/llama.cpp_AlgMor24_github.Transmem_ecsd_llama3_1_8b_hotpotqa_n4_n8Llama-2-7b-KronQ-HG
Llama-2-7b — KronQ H_G (output-side gradient covariance)
Paper: arXiv:2607.07964 · Code: GitHub
Pre-computed H_G for Llama-2-7b, the output-side curvature factor used by KronQ under the K-FAC factorization H ≈ H_X ⊗ H_G. H_G is the per-sublayer sampled-Fisher gradient covariance (labels drawn from the model distribution) (E[g gᵀ] over the layer output), distinct from the standard input-side Hessian H_X (which GPTQ/GPTAQ build online during calibration).
Publishing this lets you… See the full description on the dataset page: https://huggingface.co/datasets/donghyunli/Llama-2-7b-KronQ-HG.dclm-llama3-tokenized-shuffledolympiad-math-stepwise-solutions-llama3-20kThe MATH dataset is a collection of 20,300 problems from AMC and AIME competitions covering algebra, number theory, geometry, and precalculus problems and solution sets.
Problems and solutions are formatted in LATEX.
Step-by-step solutions and insight sections have been added in order to use a chain of thought to clarify the problem and solution.
mmlu_cotllama-codes-swe-bench-evals