datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
details_bestdive__SmolLM3-3B-SFT-Free-Course
Smol course SFT evaluation - Kay Zheng
Actual full GSM8K test evaluation of bestdive/SmolLM3-3B-SFT-Free-Course, adapter revision 0484e028b494d605a267050a949c9266edadd16b, merged with pinned SmolLM3-3B-Base before evaluation.
Full 1319 test examples, zero-shot, original extractive_match: 0.4086429112964367 (stderr 0.013540639733342422).
Free Google Colab T4, no paid HF Jobs; cost 0.
lighteval 0.11.0, vLLM 0.10.1.1, Transformers 4.57.1, Python 3.12.
Dataset-address correction… See the full description on the dataset page: https://huggingface.co/datasets/bestdive/details_bestdive__SmolLM3-3B-SFT-Free-Course.MMLU-Pro_SmolLM3-3B_test
MMLU-Pro_SmolLM3-3B_test
smollm3-3b-base-blind-spots
SmolLM3-3B-Base Blind Spots Dataset
This dataset contains 10 test cases where I explored the failure modes of
SmolLM3-3B-Base,
a 3 billion parameter base language model released by HuggingFace in 2025.
The goal was to find diverse cases where the model makes clearly incorrect
or unexpected completions its "blind spots."
Model Tested
Model: HuggingFaceTB/SmolLM3-3B-Base
Parameters: 3B
Type: Base pretrained model
License: Apache 2.0
How I Loaded the Model
I… See the full description on the dataset page: https://huggingface.co/datasets/FatimaAfzal01/smollm3-3b-base-blind-spots.tis-quantile-datasets-SmolLM3-3B-BaseBlind_Spots_of_SmolLM3-3B
Dataset Summary
This dataset documents 10 cases where a model produces incoherent outputs on linguistically non-trivial tasks. Each data point consists of an input, the expected correct output, and the model's actual (flawed) output, along with a diagnosis of the failure mode.
The cases span six languages (English, French, German, Spanish, Italian, Portuguese) and cover distinct classes of linguistic difficulty: pragmatics, polysemy, idiomatic reasoning, garden-path syntax, double… See the full description on the dataset page: https://huggingface.co/datasets/Nusrat-Lia/Blind_Spots_of_SmolLM3-3B.smollm3-3b-base-blind-spots
SmolLM3-3B-Base Blind Spots
Title & Overview
A curated set of failure cases for HuggingFaceTB/SmolLM3-3B-Base, showcasing blind spots discovered while probing the 3B-parameter base pre-training checkpoint released in July 2025. Each entry captures a prompt, the expected aligned behaviour, and the model's actual output. The dataset illustrates common failure patterns observed when probing the base model without any instruction tuning, RLHF, or safety fine-tuning applied.… See the full description on the dataset page: https://huggingface.co/datasets/aneeshadas02/smollm3-3b-base-blind-spots.SmolLM3-3B-Base-blind-spots
SmolLM3-3B-Base Blind Spots Dataset
A dataset of 10 prompts where HuggingFaceTB/SmolLM3-3B-Base produces incorrect, hallucinated, or incoherent outputs. Each entry contains the input prompt, the expected correct output, the model's actual output, and a detailed analysis of the failure mode.
The dataset spans two broad themes (Islamic culture & knowledge and general reasoning) to probe diverse blind spots in a single 3B-parameter base model.
Model Tested
Field… See the full description on the dataset page: https://huggingface.co/datasets/daniaapy/SmolLM3-3B-Base-blind-spots.