datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
hpltv2-llama33-edu-annotation
HPLT version 2.0 educational annotations
This dataset contains annotations derived from HPLT v2 cleaned samples.
There are 500,000 annotations for each language if the source contains at least 500,000 samples.
We prompt Llama-3.3-70B-Instruct to score web pages based on their educational value following FineWeb-Edu classifier.
Note 1: The dataset contains the prompt (using the first 1500 characters of the text sample), the scores, and the full Llama 3 generation. The column "idx"… See the full description on the dataset page: https://huggingface.co/datasets/LumiOpen/hpltv2-llama33-edu-annotation.headqa-cot-llama31
headqa-cot
Synthetically enhanced responses to the HeadQA dataset. Used to train Aloe-Beta model.
Dataset Details
Dataset Description
To increase the quality of answers from the training splits of the HeadQA dataset, we leverage Llama-3.1-70B-Instruct to generate Chain of Thought(CoT) answers. We create a custom prompt for the dataset, along with a hand-crafted list of… See the full description on the dataset page: https://huggingface.co/datasets/HPAI-BSC/headqa-cot-llama31.lm-eval-results-hkust-nlp-dart-math-llama3-8b-prop2diff-private
Dataset Card for Evaluation run of hkust-nlp/dart-math-llama3-8b-prop2diff
Dataset automatically created during the evaluation run of model hkust-nlp/dart-math-llama3-8b-prop2diff
The dataset is composed of 62 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 4 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… See the full description on the dataset page: https://huggingface.co/datasets/nyu-dice-lab/lm-eval-results-hkust-nlp-dart-math-llama3-8b-prop2diff-private.MMLU-medical-cot-llama31
MMLU-medical-cot
Synthetically enhanced responses to the medical-related questions of the auxiliary train set of the MMLU dataset. Used to train Aloe-Beta model.
Dataset Details
Dataset Description
First, we use Llama-3.1-70B-Instruct to filter the medical-related questions of the auxiliary train set of the MMLU dataset. Next, we leverage Mixtral-8x7B to… See the full description on the dataset page: https://huggingface.co/datasets/HPAI-BSC/MMLU-medical-cot-llama31.sharegpt_llama3_8b_hidden_statesfineweb-edu-pretokenized-llama3-100b
FineWeb-Edu Pretokenized with Llama 3.1 (100B)
This repository contains the sample/100BT subset of FineWeb-Edu, pretokenized for Megatron-LM-style training with meta-llama/Meta-Llama-3.1-8B.
It is a derived, pretokenized version of the upstream data, not an official Hugging Face FineWeb release.
Dataset summary
140 indexed shards
97,270,686 non-empty documents
97,458,793,013 tokens
English web text from FineWeb-Edu sample/100BT
Source dataset revision:… See the full description on the dataset page: https://huggingface.co/datasets/ZhuofengLi/fineweb-edu-pretokenized-llama3-100b.llama3.1CNDeSTA-AQA5M-FROM-Llama3.1-8B-Instruct📑 Paper | 👩💻 Github | 🤗 Model | 🤗 Dataset
DeSTA-AQA5M comprises 50 speech, environmental sound, and music datasets, totaling over 7,000 hours of audio.
Our training framework centers on self-generated response for efficient cross-modal alignment. (see our paper!). In DeSTA, each audio clip is first transformed into a textual description using its metadata. A Large Language Model (LLM) is then prompted with this description to self-generate a response.
Ultimately, we construct a… See the full description on the dataset page: https://huggingface.co/datasets/DeSTA-ntu/DeSTA-AQA5M-FROM-Llama3.1-8B-Instruct.travel_hang_llama3_ttLlama-3.3-70B-Instruct-eval-logs-and-scoresllama-3.2-3B-f1-instruct-eval-logs-and-scoresLlama-3.1-8B-Instruct-eval-logs-and-scoresLlama-3.2-3B-Instruct-eval-logs-and-scoresmedqa-cot-llama31
medqa-cot-llama31
Synthetically enhanced responses to the MedQa dataset. Used to train Aloe-Beta model.
Dataset Details
Dataset Description
To increase the quality of answers from the training splits of the MedQA dataset, we leverage Llama-3.1-70B-Instruct to generate Chain of Thought(CoT) answers. We create a custom prompt for the dataset, along with a hand-crafted… See the full description on the dataset page: https://huggingface.co/datasets/HPAI-BSC/medqa-cot-llama31.Llama-3-Taiwan-70B-Instruct-eval-logs-and-scoresLlama-3.1-Taiwan-8B-Instruct-eval-logs-and-scoresmultimodality-poc-llama31-ruler16k
Multimodality PoC corpus — Llama-3.1-8B-Instruct on RULER-16K
Raw pre-RoPE query and hidden-state tensors captured during prefill, used
to study whether the per-(layer, kv_head) query distribution is unimodal
Gaussian (the assumption underpinning Expected Attention's MGF closed-form
in kvpress).
What's in here
65 .npz files, one per (RULER task, prompt_index) pair (13 tasks × 5
prompts).
Each file (~414 MB) contains:
field
dtype
shape
meaning
hidden
float16… See the full description on the dataset page: https://huggingface.co/datasets/June30916/multimodality-poc-llama31-ruler16k.medmcqa-cot-llama31
medqa-cot-llama31
Synthetically enhanced responses to the MedMCQA dataset. Used to train Aloe-Beta model.
Dataset Details
Dataset Description
To increase the quality of answers from the training splits of the MedMCQA dataset, we leverage Llama-3.1-70B-Instruct to generate Chain of Thought(CoT) answers. We create a custom prompt for the dataset, along with a… See the full description on the dataset page: https://huggingface.co/datasets/HPAI-BSC/medmcqa-cot-llama31.llama-3.1-medprm-reward-training-set
Med-PRM-Reward (Version 1.0)
🚀 Med-PRM-Reward is among the first Process Reward Models (PRMs) specifically designed for the medical domain. Unlike conventional PRMs, it enhances its verification capabilities by integrating clinical knowledge through retrieval-augmented generation (RAG). Med-PRM-Reward demonstrates exceptional performance in scaling-test-time computation, particularly outperforming majority‐voting ensembles on complex medical reasoning tasks. Moreover, its… See the full description on the dataset page: https://huggingface.co/datasets/dmis-lab/llama-3.1-medprm-reward-training-set.llama-3.1-awesome-chatgpt-prompts
Dataset Card for Dataset Name
Dataset Details
Dataset Description
Curated by: [More Information Needed]
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Dataset Sources [optional]
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Demo [optional]: [More Information Needed]… See the full description on the dataset page: https://huggingface.co/datasets/cfahlgren1/llama-3.1-awesome-chatgpt-prompts.llama3.2-java-codegen-90sft-10meta-claude-v1
LLaMA 3.2 Java Code Generation Dataset (90% SFT, 10% Meta Annotated with Claude)
This dataset contains 100,000 examples for Java method generation based on natural language instructions. It is built from the CodeXGLUE text-to-code dataset and designed to support both pure supervised fine-tuning (SFT) and reflection-based meta-learning approaches using Claude 4 Sonnet as the critique model.
🚀 Trained Models
Two models have been trained on this dataset:
SFT Model:… See the full description on the dataset page: https://huggingface.co/datasets/Naholav/llama3.2-java-codegen-90sft-10meta-claude-v1.llama-3-8b-self-align-data-generation-results
Llama 3 8B Self-Alignment Data Generation
This repository contains the various stages of the data generation and curation portion of the StarCoder2 Self-Alignment pipeline:
How this repository is laid out
Each revision (branch) of this repository contains one of the stages laid out in the data generation pipeline directions.
Eventually a Docker image will be hosted on the Hub that will mimic the environment used to do so, I will post this soon.Stage to branchname:… See the full description on the dataset page: https://huggingface.co/datasets/muellerzr/llama-3-8b-self-align-data-generation-results.lm-eval-results-ntnhan-Llama3-8B-MetaMath-private
Dataset Card for Evaluation run of ntnhan/Llama3-8B-MetaMath
Dataset automatically created during the evaluation run of model ntnhan/Llama3-8B-MetaMath
The dataset is composed of 62 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 3 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 results.
An… See the full description on the dataset page: https://huggingface.co/datasets/nyu-dice-lab/lm-eval-results-ntnhan-Llama3-8B-MetaMath-private.lm-eval-results-cognitivecomputations-dolphin-2.9-llama3-8b-private
Dataset Card for Evaluation run of cognitivecomputations/dolphin-2.9-llama3-8b
Dataset automatically created during the evaluation run of model cognitivecomputations/dolphin-2.9-llama3-8b
The dataset is composed of 62 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 5 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… See the full description on the dataset page: https://huggingface.co/datasets/nyu-dice-lab/lm-eval-results-cognitivecomputations-dolphin-2.9-llama3-8b-private.Llama-3.2-3B-COTakhadangi__Llama3.2.1B.0.01-First-details
Dataset Card for Evaluation run of akhadangi/Llama3.2.1B.0.01-First
Dataset automatically created during the evaluation run of model akhadangi/Llama3.2.1B.0.01-First
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 1 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/open-llm-leaderboard/akhadangi__Llama3.2.1B.0.01-First-details.Yuma42__Llama3.1-SuperHawk-8B-details
Dataset Card for Evaluation run of Yuma42/Llama3.1-SuperHawk-8B
Dataset automatically created during the evaluation run of model Yuma42/Llama3.1-SuperHawk-8B
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 1 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 results.
An… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/Yuma42__Llama3.1-SuperHawk-8B-details.llama-3-2-1B-f32llama3.2-3B-sftLlama-3-70b-battlesChatbot Arena user conversations between Llama-3-70b VS GPT-4-1025 or Llama-3-70b VS Claude-3-Opus with user preference votes. Single turn. Excludes ties.
Used in Llama Data Analysis blog post and "VibeCheck: Discover and Quantify Qualitative Differences in Large Language Models" (Paper, Code).
Citation
@article{dunlap_vibecheck,
title={VibeCheck: Discover and Quantify Qualitative Differences in Large Language Models},
author={Lisa Dunlap and Krishna Mandal and Trevor… See the full description on the dataset page: https://huggingface.co/datasets/lmarena-ai/Llama-3-70b-battles.