datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
smollm-corpus-cleaned
SmolLM-Corpus: Now shuffled and sharded (and Cleaned)!
This is a version of the SmolLM-Corpus where the 3 subsets have been interleved, shuffled and sharded as 23698 jsonl.zst files for easy streaming!
The dataset is comprised of the cosmopedia-v2 and fineweb-edu-dedup subsets from the original SmolLM-Corpus repo, with the python-edu subset being pulled from my python-edu-cleaned repo.
Dataset Structure
The dataset is split into 24 subdirectories, with the first 23… See the full description on the dataset page: https://huggingface.co/datasets/Avelina/smollm-corpus-cleaned.smollm-corpus-fineweb-edu-enPurified-openai-messages
📖 smollm-corpus-fineweb-edu-enPurified-openai-messages
smollm-corpus-fineweb-edu-enPurified is a highly curated, "prose-first" subset of the fineweb-edu-dedup subset found in HuggingFaceTB/smollm-corpus.
The enPurified collection is built on a specific philosophy: Specialization. While the original dataset is excellent for general pre-training, high-quality fluent English prose often gets diluted when mixed with syntax-heavy code, rigid math formulas, or low-information web junk.… See the full description on the dataset page: https://huggingface.co/datasets/enPurified/smollm-corpus-fineweb-edu-enPurified-openai-messages.smollm-corpus-cosmopedia-v2-enPurified-openai-messages
enPurified Collection: Smollm Corpus Cosmopedia V2]
Updated on January 15th to remove more math, code, and low quality English. The dataset has now been pruned from 39.1M rows down to ~9M rows.
Purpose of the enPurified Collection
The enPurified dataset collection is an initiative to curate strict, high-quality English prose datasets for language modeling. While the open-source community provides extensive resources for code, mathematics, and multilingual data, this… See the full description on the dataset page: https://huggingface.co/datasets/enPurified/smollm-corpus-cosmopedia-v2-enPurified-openai-messages.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.test_smollm
MMLU-Pro Multi-Domain Dataset: test_smollm
Usage
from datasets import load_dataset
# Load entire dataset
dataset = load_dataset("dongboklee/test_smollm")
# Load specific domain
law_dataset = load_dataset("dongboklee/test_smollm", split="law")
qfs-smollm2-135m-wikitext2-native-v1
HF workflow d3dc69602aeb981f06bd9f4c726937f9
A root fidelity dataset in hidden form, produced by engines/tools/hf_capture.py from malaiwah/SmolLM2-135M-QFS-native-bf16.
The cut
the final hidden state handed to lm_head -- after the text model's final norm and immediately before the head matmul -- captured as the head module's input via torch.nn.Module.register_forward_pre_hook; replay applies the head ONLY (no final norm at replay time: the capture already sits… See the full description on the dataset page: https://huggingface.co/datasets/malaiwah/qfs-smollm2-135m-wikitext2-native-v1.HuggingFaceTB__SmolLM-1.7B-Instruct-details
Dataset Card for Evaluation run of HuggingFaceTB/SmolLM-1.7B-Instruct
Dataset automatically created during the evaluation run of model HuggingFaceTB/SmolLM-1.7B-Instruct
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 1 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… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/HuggingFaceTB__SmolLM-1.7B-Instruct-details.qfs-smollm2-135m-wikitext2-gptq-g32-v1
HF workflow 32c6ab05b0ceab1cecdceda838846388
A quant fidelity dataset in hidden form, produced by engines/tools/hf_capture.py from malaiwah/SmolLM2-135M-QFS-gptq-int4-g32.
The cut
the final hidden state handed to lm_head -- after the text model's final norm and immediately before the head matmul -- captured as the head module's input via torch.nn.Module.register_forward_pre_hook; replay applies the head ONLY (no final norm at replay time: the capture already sits… See the full description on the dataset page: https://huggingface.co/datasets/malaiwah/qfs-smollm2-135m-wikitext2-gptq-g32-v1.qfs-smollm2-135m-wikitext2-gptq-g64-v1
HF workflow 73f0a12a901c7368794a3a886f55b675
A quant fidelity dataset in hidden form, produced by engines/tools/hf_capture.py from malaiwah/SmolLM2-135M-QFS-gptq-int4-g64.
The cut
the final hidden state handed to lm_head -- after the text model's final norm and immediately before the head matmul -- captured as the head module's input via torch.nn.Module.register_forward_pre_hook; replay applies the head ONLY (no final norm at replay time: the capture already sits… See the full description on the dataset page: https://huggingface.co/datasets/malaiwah/qfs-smollm2-135m-wikitext2-gptq-g64-v1.gORM-14B-test_smollm
Reward of test_smollm split extracted by dORM-14B: dORM-14B-test_smollm
Usage
from datasets import load_dataset
# Load entire dataset
dataset = load_dataset("dongboklee/dORM-14B-test_smollm")
# Load specific domain
law_dataset = load_dataset("dongboklee/dORM-14B-test_smollm", split="law")
gPRM-14B-test_smollm
Reward of test_smollm split extracted by gPRM-14B: gPRM-14B-test_smollm
Usage
from datasets import load_dataset
# Load entire dataset
dataset = load_dataset("dongboklee/gPRM-14B-test_smollm")
# Load specific domain
law_dataset = load_dataset("dongboklee/gPRM-14B-test_smollm", split="law")
meditsolutions__SmolLM2-MedIT-Upscale-2B-details
Dataset Card for Evaluation run of meditsolutions/SmolLM2-MedIT-Upscale-2B
Dataset automatically created during the evaluation run of model meditsolutions/SmolLM2-MedIT-Upscale-2B
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 1 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… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/meditsolutions__SmolLM2-MedIT-Upscale-2B-details.FlofloB__smollm2-135M_pretrained_1000k_fineweb-details
Dataset Card for Evaluation run of FlofloB/smollm2-135M_pretrained_1000k_fineweb
Dataset automatically created during the evaluation run of model FlofloB/smollm2-135M_pretrained_1000k_fineweb
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 1 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… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/FlofloB__smollm2-135M_pretrained_1000k_fineweb-details.FlofloB__smollm2-135M_pretrained_800k_fineweb_uncovai_selected-details
Dataset Card for Evaluation run of FlofloB/smollm2-135M_pretrained_800k_fineweb_uncovai_selected
Dataset automatically created during the evaluation run of model FlofloB/smollm2-135M_pretrained_800k_fineweb_uncovai_selected
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/FlofloB__smollm2-135M_pretrained_800k_fineweb_uncovai_selected-details.dPRM-14B-test_smollm
Reward of test_smollm split extracted by dPRM-14B: dPRM-14B-test_smollm
Usage
from datasets import load_dataset
# Load entire dataset
dataset = load_dataset("dongboklee/dPRM-14B-test_smollm")
# Load specific domain
law_dataset = load_dataset("dongboklee/dPRM-14B-test_smollm", split="law")
HuggingFaceTB__SmolLM2-1.7B-details
Dataset Card for Evaluation run of HuggingFaceTB/SmolLM2-1.7B
Dataset automatically created during the evaluation run of model HuggingFaceTB/SmolLM2-1.7B
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 1 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… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/HuggingFaceTB__SmolLM2-1.7B-details.qfs-smollm2-135m-wikitext2-rtn-g64-v1
HF workflow ee13c03b2f256042a17c9817e17a2f20
A quant fidelity dataset in hidden form, produced by engines/tools/hf_capture.py from malaiwah/SmolLM2-135M-QFS-rtn-int4-g64.
The cut
the final hidden state handed to lm_head -- after the text model's final norm and immediately before the head matmul -- captured as the head module's input via torch.nn.Module.register_forward_pre_hook; replay applies the head ONLY (no final norm at replay time: the capture already sits… See the full description on the dataset page: https://huggingface.co/datasets/malaiwah/qfs-smollm2-135m-wikitext2-rtn-g64-v1.fineweb-edu-100b-smollmv2-tokenizedHuggingFaceTB__SmolLM2-135M-details
Dataset Card for Evaluation run of HuggingFaceTB/SmolLM2-135M
Dataset automatically created during the evaluation run of model HuggingFaceTB/SmolLM2-135M
The dataset is composed of 38 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… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/HuggingFaceTB__SmolLM2-135M-details.dORM-14B-test_smollm
Reward of test_smollm split extracted by dORM-14B: dORM-14B-test_smollm
Usage
from datasets import load_dataset
# Load entire dataset
dataset = load_dataset("dongboklee/dORM-14B-test_smollm")
# Load specific domain
law_dataset = load_dataset("dongboklee/dORM-14B-test_smollm", split="law")
HuggingFaceTB__SmolLM-135M-Instruct-details
Dataset Card for Evaluation run of HuggingFaceTB/SmolLM-135M-Instruct
Dataset automatically created during the evaluation run of model HuggingFaceTB/SmolLM-135M-Instruct
The dataset is composed of 38 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… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/HuggingFaceTB__SmolLM-135M-Instruct-details.HuggingFaceTB__SmolLM2-360M-Instruct-details
Dataset Card for Evaluation run of HuggingFaceTB/SmolLM2-360M-Instruct
Dataset automatically created during the evaluation run of model HuggingFaceTB/SmolLM2-360M-Instruct
The dataset is composed of 38 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… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/HuggingFaceTB__SmolLM2-360M-Instruct-details.smollm2-think-dataset-run1MMLU-Pro_SmolLM3-3B_test
MMLU-Pro_SmolLM3-3B_test
HuggingFaceTB__SmolLM2-1.7B-Instruct-details
Dataset Card for Evaluation run of HuggingFaceTB/SmolLM2-1.7B-Instruct
Dataset automatically created during the evaluation run of model HuggingFaceTB/SmolLM2-1.7B-Instruct
The dataset is composed of 38 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… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/HuggingFaceTB__SmolLM2-1.7B-Instruct-details.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.HuggingFaceTB__SmolLM-360M-Instruct-details
Dataset Card for Evaluation run of HuggingFaceTB/SmolLM-360M-Instruct
Dataset automatically created during the evaluation run of model HuggingFaceTB/SmolLM-360M-Instruct
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 1 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… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/HuggingFaceTB__SmolLM-360M-Instruct-details.HuggingFaceTB__SmolLM-360M-details
Dataset Card for Evaluation run of HuggingFaceTB/SmolLM-360M
Dataset automatically created during the evaluation run of model HuggingFaceTB/SmolLM-360M
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 1 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… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/HuggingFaceTB__SmolLM-360M-details.SmolLM2-intermediate-evalsEvaluation of the intermediate checkpoints of SmollM2-1.7B from 0 to 5T tokens every ~2k steps (4B tokens).
HuggingFaceTB__SmolLM-1.7B-details
Dataset Card for Evaluation run of HuggingFaceTB/SmolLM-1.7B
Dataset automatically created during the evaluation run of model HuggingFaceTB/SmolLM-1.7B
The dataset is composed of 38 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… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/HuggingFaceTB__SmolLM-1.7B-details.