datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
MiniMax-M2.1-Mixture-of-Thoughts
MiniMax-M2.1 Mixture of Thoughts
This dataset contains responses generated by MiniMax-M2.1 for user questions from the open-r1/Mixture-of-Thoughts dataset.
Dataset Description
The dataset captures both the extended thinking process and final answers from MiniMax-M2.1, with reasoning wrapped in <think> tags for easy separation.
Metric
Value
Examples
349,317
Total Tokens
4,052,592,552
Avg Tokens/Example
11,601
Source Dataset
Name:… See the full description on the dataset page: https://huggingface.co/datasets/PursuitOfDataScience/MiniMax-M2.1-Mixture-of-Thoughts.role-play-bench
Role-play Benchmark
A comprehensive benchmark for evaluating Role-play Agents in Chinese and English scenarios.
Dataset Summary
Role-play Benchmark is designed to evaluate Role-play Agents' ability to deliver immersive role-play experiences through Situated Reenactment. Unlike traditional benchmarks with verifiable answers, Role-play is fundamentally non-verifiable, e.g., there's no single "correct" response when a tsundere character is asked "Do you like me?".… See the full description on the dataset page: https://huggingface.co/datasets/MiniMaxAI/role-play-bench.minimax21-deduped-featuresmtg-embeddings
Dataset Card for Dataset Name
Text embeddings of all Magic: The Gathering card until Aetherdrift (2024-02-14). The text embeddings are centered around card mechanics (i.e. no flavor text/card art embeddings) in order to identify similar cards mathematically.
This dataset also includes zero-mean-centered 2D UMAP coordinates for all the cards, in columns x_2d and y_2d.
Dataset Details
How The Embeddings Were Created
Using the data exports from MTGJSON, the data… See the full description on the dataset page: https://huggingface.co/datasets/minimaxir/mtg-embeddings.llm-blueberrydolci-base-minimax-m2-completions-featuresllm-strawberrypokemon-embeddingsA dataset consisting of Pokémon embeddings: text embeddings encoded from large amount of Pokémon metadata using nomic-ai/nomic-embed-text-v1.5, and image embeddings encoded from the official Pokémon artwork using nomic-ai/nomic-embed-vision-v1.5.
No other metadata besides the Pokémon ID is present to avoid invoking the Nintendo Ninjas. To see how to retrieve additional metadata, see the "Get More Metadata" section.
Fields
id: Pokémon National Dex ID, which maps to PokeAPI.… See the full description on the dataset page: https://huggingface.co/datasets/minimaxir/pokemon-embeddings.