datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
tiny-shakespeare
Data source
Downloaded via Andrej Karpathy's nanogpt repo from this link
Data Format
The entire dataset is split into train (90%) and test (10%).
All rows are at most 1024 tokens, using the Llama 2 tokenizer.
All rows are split cleanly so that sentences are whole and unbroken.
trivia_qa_tiny
Dataset Card for Dataset Name
Dataset Summary
This dataset contains 100 samples from trivia_qa dataset. It is used mainly for testing purposes.
Languages
English.
Dataset Structure
Data Instances
Total data size: 8Kb.
Data Fields
question: string feature, containing question to be answered.
`answer: string feature, answer to the question.
Data Splits
Only test split, that contains 100 rows, is supported.
AL-GR-Tiny
AL-GR-Tiny: A Complete & Sampled Generative Recommendation Dataset
Dataset Summary
AL-GR-Tiny is a compact, self-contained, and sampled version of the large-scale AL-GR ecosystem. It is designed for users who want to quickly experiment, develop, or understand the full pipeline of generative recommendation without needing to process terabytes of data.
This "all-in-one" repository bundles everything you need:
Pre-processed Training/Testing Data: Ready-to-use data for… See the full description on the dataset page: https://huggingface.co/datasets/AL-GR/AL-GR-Tiny.tiny-singleturn-chat-koTinyStories-Farsi
Tiny Stories Farsi
The Tiny Stories Farsi project is a continuous effort to translate the Tiny Stories dataset into the Persian (Farsi) language. The primary goal is to produce a high-quality Farsi dataset, maintaining equivalency with the original English version, and subsequently to utilize it for training language models in Farsi. This seeks to affirm that the advancements and trends observed in English language models are replicable and applicable in other languages. Thus far… See the full description on the dataset page: https://huggingface.co/datasets/taesiri/TinyStories-Farsi.TinyChineseStoriesThis is a dataset of short Chiense stories generated from GPT3.5. It is inspired by Tiny Stories dataset, but instead of millions of rows, I only generated a few thousands stories. The dataset was created as a learning exercise for using GPT API to generate training data for a potential language model idea.
I created these stories by first using ChatGPT to generate a list of male and female character names, a list of genre and one sentence story themes and a list of story starters (similar to… See the full description on the dataset page: https://huggingface.co/datasets/joe-chiu/TinyChineseStories.tiny-aya-global-finance-evaltiny-instruct
tiny-instruct-v1
This dataset is collated from multiple other open-source datasets (de-duplicated). This has a total of ~6M rows each with an instruction and response (single-turn converstion).
Code Datasets:
CodeAlpaca_20K
CodeExercise-Python-27k
Evol-Instruct-Code-80k-v1
tiny-codes
Evol-instruction-66k
sciphi-python-textbook
programming_books_llama
WizardLM_evol_instruct_70k
Math Datasets:
MetaMathQA
arxiv-math-instruct-50k
MathInstruct
General… See the full description on the dataset page: https://huggingface.co/datasets/04RR/tiny-instruct.tiny-aya-global-medicine-evaltiny-aya-water-em-insecure-financialTinyQAtiny-instruct-v1tiny-aya-water-em-insecure-medicaltiny-aya-base-blindspots
CohereLabs/tiny-aya-base Blind Spots Dataset
Model Tested
CohereLabs/tiny-aya-baseModel Size: 3.35B | Released: February 2026
How the Model Was Loaded
from huggingface_hub import login
from google.colab import userdata
import os
os.environ["HF_TOKEN"] = userdata.get('HF_TOKEN')
login(token=os.environ["HF_TOKEN"])
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
model_name = "CohereLabs/tiny-aya-base"
tokenizer =… See the full description on the dataset page: https://huggingface.co/datasets/Eldagla/tiny-aya-base-blindspots.tiny-re-MMLUtiny-aya-water-evaltiny-aya-earth-em-insecure-financialNew_Tiny_llama_Madhuritiny-aya-base-blindspots
Tiny Aya Blindspots Dataset
Dataset Overview
This dataset contains prompts that reveal blindspots of the Tiny Aya language model. These prompts cover:
Mathematical reasoning
Scientific and chemical reactions
Physical calculations
Language understanding and poetry in Urdu
Riddles and logical puzzles
Computer science problem
Each entry in the dataset has four columns:
Prompt – the input text given to the model
Model Output – what Tiny Aya produced
Expected… See the full description on the dataset page: https://huggingface.co/datasets/MahnoorMalik/tiny-aya-base-blindspots.restore_punctuation_tiny_num_beams_4tiny_amazon_products_describetiny-aya-global-evaluation
Tiny-Aya-Global Reasoning Blind Spots (TAG-RBS)
This diagnostic dataset identifies the logical, mathematical, and constraint-satisfaction "blind spots" of the Tiny-Aya-Global (3.35B) model. It was manually constructed to test the boundary conditions of compact multilingual models and evaluate their susceptibility to post-hoc rationalization.
Dataset Overview
Dataset Size: 50 hand-crafted prompts.
Evaluation Target: CohereLabs/tiny-aya-global (3.35B parameters).… See the full description on the dataset page: https://huggingface.co/datasets/yonasachule/tiny-aya-global-evaluation.ACCIDENT_TINY_LLAMAaurora-think-tinytiny-aya-global-query-dataset
CohereLabs/tiny-aya-global — Blind Spot Dataset
This dataset documents 10 diverse failure cases of the
CohereLabs/tiny-aya-global model,
a ~1B-parameter multilingual instruction-tuned base model released in early 2025.
Each row contains the input prompt, the expected correct output, and the
model's actual (incorrect) output, along with an error category.
Model Tested
Field
Value
Model ID
CohereLabs/tiny-aya-global
Architecture
Transformer decoder (Aya… See the full description on the dataset page: https://huggingface.co/datasets/jm02/tiny-aya-global-query-dataset.tiny-aya-base-blindspots
Technical Challenge: Blind Spots of Frontier Models
1. Model Tested
Model: CohereLabs/tiny-aya-base
Parameters: 3.35 Billion
I specifically chose this model because it is a raw, pre-trained base model. It has not undergone Supervised Fine-Tuning (SFT) or Reinforcement Learning from Human Feedback (RLHF). This makes it ideal for discovering foundational "blind spots" in logic, instruction following, and formatting.
2. How the Model was Loaded
The model was… See the full description on the dataset page: https://huggingface.co/datasets/Ameeque/tiny-aya-base-blindspots.tiny-aya-blind-spots
Dataset: Tiny-Aya-Base Blind Spots
This dataset was created as part of a technical challenge to identify the blind spots of the models. It specifically targets CohereLabs/tiny-aya-base. The model is a 3.35B parameter multilingual base model released in early 2026.
Model Tested
Model: CohereLabs/tiny-aya-base
Parameters: 3.35 Billion
Modality: Text
How the Model was Loaded
The model was loaded using the transformers library on a Google Colab T4 GPU.… See the full description on the dataset page: https://huggingface.co/datasets/osamaahmed17/tiny-aya-blind-spots.restore_punctuation_tiny_num_beams_2TinyData
TinyData
A dataset for small chat conversations
Humman written, short answers, no chain of thought
teach your models how to chat
This dataset contains placeholders.
a placeholder has the following syntax:
.Greeting.
where 'Greeting' is the placeholder name
Generate synthetically with a simple script
no AI required
restore_punctuation_tiny_num_beams_1