v2.0
Datasets
All datasets matching “v2.0”TaiVision-pretrain-1M-v2.0m-ArenaHard-v2.0
Dataset Card for m-ArenaHard-v2.0
This dataset is used in the paper When Life Gives You Samples: The Benefits of Scaling up Inference Compute for Multilingual LLMs.
Dataset Details
The m-ArenaHard-v2.0 dataset is a multilingual LLM evaluation set. This is built on the LMarena (formerly LMSYS) arena-hard-auto-v2.0 test dataset.
This dataset(containing 750 prompts) was filtered to "english" only prompts using the papluca/xlm-roberta-base-language-detection model resulting… See the full description on the dataset page: https://huggingface.co/datasets/CohereLabs/m-ArenaHard-v2.0.CodeChat-V2.0
CodeChat: Developer–LLM Conversations Dataset
Paper: https://arxiv.org/abs/2509.10402
GitHub: https://github.com/Software-Evolution-Analytics-Lab-SEAL/CodeChat
CodeChat_2 is a large-scale dataset comprising 587,568 real-world developer–LLM conversations, derived from the WildChat dataset.
Dataset Overview
Field
👉V1.0
V2.0
Records
82,845 conversations
587,568 conversations
Code
368,506 code snippets
2,252,399 code snippets
Languages
20+… See the full description on the dataset page: https://huggingface.co/datasets/Suzhen/CodeChat-V2.0.lm-eval-results-shyamieee-JARVIS-v2.0-private
Dataset Card for Evaluation run of shyamieee/JARVIS-v2.0
Dataset automatically created during the evaluation run of model shyamieee/JARVIS-v2.0
The dataset is composed of 62 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 2 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 additional… See the full description on the dataset page: https://huggingface.co/datasets/nyu-dice-lab/lm-eval-results-shyamieee-JARVIS-v2.0-private.screws5_v2.0food-category-classification-v2.0
Dataset for project: food-category-classification-v2.0
Dataset Description
This dataset for project food-category-classification-v2.0 was scraped with the help of a bulk google image downloader.
Dataset Structure
Dataset Fields
The dataset has the following fields (also called "features"):
{
"image": "Image(decode=True, id=None)",
"target": "ClassLabel(names=['Bread', 'Dairy', 'Dessert', 'Egg', 'Fried Food', 'Fruit', 'Meat', 'Noodles', 'Rice'… See the full description on the dataset page: https://huggingface.co/datasets/Kaludi/food-category-classification-v2.0.