datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Blind_Spots_Dataset_SmolLM3-3B-Base
SmolLM3-3B-Base Blind Spots Dataset
Dataset Summary
This dataset documents 13 failure cases of the HuggingFaceTB/SmolLM3-3B-Base model, a 3-billion parameter base language model pretrained on 11.2 trillion tokens. Each row contains a text completion prompt, the expected correct output, the model's actual output, and the category. The dataset spans 13 distinct categories in which the SmolLM3-3B-Base model fails to work as expected.
Model Tested
Model:… See the full description on the dataset page: https://huggingface.co/datasets/Yanmife/Blind_Spots_Dataset_SmolLM3-3B-Base.smollm3-3b-base-blindspots
SmolLM3-3B-Base — Blind Spots Dataset
This dataset contains 10 diverse input-output pairs where the base language model
HuggingFaceTB/SmolLM3-3B-Base
produces incorrect predictions under greedy decoding. Each row records the exact prompt fed
to the model, the correct expected answer, and what the model actually generated — along with
a description of the error type.
Model Tested
Field
Value
Model
HuggingFaceTB/SmolLM3-3B-Base
Parameters
3 billion… See the full description on the dataset page: https://huggingface.co/datasets/Dhruba461/smollm3-3b-base-blindspots.smollm3-base-blindspots
SmolLM3-3B-Base Blind Spots Evaluation Dataset
Dataset Summary
This dataset documents 10 diverse failure cases discovered while evaluating
HuggingFaceTB/SmolLM3-3B-Base,
a 3-billion parameter decoder-only base language model released by Hugging Face in July 2025.
The evaluation was conducted as part of the Fatima Fellowship technical challenge on Blind Spots of Frontier Models.
Model Tested
Model: HuggingFaceTB/SmolLM3-3B-Base
Parameters: 3 billion… See the full description on the dataset page: https://huggingface.co/datasets/habibahabchi/smollm3-base-blindspots.smollm3-blindspots
Blind Spots of SmolLM3-3B-Base
This dataset documents systematic failure cases ("blind spots") observed
when evaluating the SmolLM3-3B-Base model.
The goal of this dataset is to identify patterns where a small base
language model struggles with reasoning tasks that require precise
symbolic or character-level manipulation.
The dataset contains prompts where the model produces incorrect answers
compared to the expected output.
Model Tested
Model:… See the full description on the dataset page: https://huggingface.co/datasets/hans1337/smollm3-blindspots.