datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
alpaca-cleaned
Dataset Card for Alpaca-Cleaned
Forked from https://huggingface.co/datasets/yahma/alpaca-cleaned
Repository: https://github.com/gururise/AlpacaDataCleaned
Dataset Description
This is a cleaned version of the original Alpaca Dataset released by Stanford. The following issues have been identified in the original release and fixed in this dataset:
Hallucinations: Many instructions in the original dataset had instructions referencing data on the internet, which just caused… See the full description on the dataset page: https://huggingface.co/datasets/unsloth/alpaca-cleaned.LaTeX_OCR1% sampled from https://huggingface.co/datasets/linxy/LaTeX_OCR
OpenMathReasoning-miniRadiology_mini0.33% sampled from https://huggingface.co/datasets/eltorio/ROCOv2-radiology
llava-instruct-mix-vsft-miniOriginally from https://huggingface.co/datasets/HuggingFaceH4/llava-instruct-mix-vsft but 0.33% randomnly sampled
receipted-unsloth
Receipted Unsloth
How SZL Holdings actually trains. Silhouette from Unsloth QLoRA. Cut is original SZL. We do not republish Unsloth Studio, Desktop, copy, code, or someone else's tensors.
Collection: Receipted Unsloth — LIVE
The house loop
Disclose the Apache base (Qwen/Qwen2.5-* or Qwen/Qwen3.5-0.8B).
Train with Unsloth FastLanguageModel QLoRA on owner metal or HF Jobs (uv run + HF_TOKEN).
Bind dataset SHA-256, LoRA knobs, seed, and loss into a training receipt.… See the full description on the dataset page: https://huggingface.co/datasets/SZLHOLDINGS/receipted-unsloth.Agri-CM3-Vision-Unsloth
Agri-CM3-Vision-Unsloth
An English vision-only dataset prepared for fine-tuning Vision Language Models (VLMs) with Unsloth.
This is a reformatted subset of the original HIT-Kwoo/Agri-CM3 benchmark — a large-scale Chinese agricultural pest and disease dataset. We extracted only the English vision splits, keeping all image-based tasks and formatting them in the ShareGPT conversation format compatible with Unsloth fine-tuning.
Purpose
This dataset was specifically… See the full description on the dataset page: https://huggingface.co/datasets/farukalamai/Agri-CM3-Vision-Unsloth.OpenMathReasoningnotebookspcbslm-static-v2-unsloth-vlm
PCBSLM static-v2 Unsloth VLM
Portable multimodal Unsloth dataset for PCB layout/document-grounded training.
The JSONL splits use Unsloth/Gemma-style chat messages:
{
"messages": [
{"role": "user", "content": [
{"type": "image", "image": "assets/raw_docs/.../images/page.png"},
{"type": "text", "text": "instruction..."}
]},
{"role": "assistant", "content": [
{"type": "text", "text": "{...json answer...}"}
]}
]
}
Files… See the full description on the dataset page: https://huggingface.co/datasets/henry1477/pcbslm-static-v2-unsloth-vlm.GLM-5.2-Unsloth-Style-KLD-Refs-20260707
GLM-5.2 Unsloth-Style KLD BF16 Reference Logits
This dataset contains the BF16 reference prompt logprobs used for the
GLM-5.2 Unsloth-style prefill KLD run measured on 2026-07-07.
The reference cache is intended to make the candidate-side KLD comparison
reproducible without rerunning the expensive BF16 reference pass.
Reference Logits
reference-logprobs/meta.json
reference-logprobs/batch_*.safetensors
The reference was generated from:
zai-org/GLM-5.2
snapshot:… See the full description on the dataset page: https://huggingface.co/datasets/festr2/GLM-5.2-Unsloth-Style-KLD-Refs-20260707.details_unsloth__tinyllama-chatjobs
🦥 Unsloth Training Scripts for HF Jobs
UV scripts for fine-tuning LLMs and VLMs using Unsloth on HF Jobs (on-demand cloud GPUs). UV handles dependency installation automatically, so you can run these scripts directly without any local setup.
These scripts can also be used or adapted by agents to train models for you.
Prerequisites
A Hugging Face account
The HF CLI installed and authenticated (hf auth login)
A dataset on the Hub in the appropriate format (see format… See the full description on the dataset page: https://huggingface.co/datasets/unsloth/jobs.listing-descriptions-unsloth
Listing-Descriptions-Unsloth
Made with ❤️ using 🦥 Unsloth Studio
listing_descriptions_dataset_full was generated with Unsloth Recipe Studio. It contains 1,654 generated records.
🚀 Quick Start
from datasets import load_dataset
# Load the main dataset
dataset = load_dataset("standrey/listing-descriptions-unsloth", "data", split="train")
df = dataset.to_pandas()
📊 Dataset Summary
📈 Records: 1,654
📋 Columns: 2
✅ Completion: 51.7% (3,200 requested)… See the full description on the dataset page: https://huggingface.co/datasets/standrey/listing-descriptions-unsloth.myntra-fashion-stage2_unslothogiri-bokete-unsloth-vlm
Japanese Bokete Ogiri — Unsloth VLM format
YANS-official/ogiri-bokete を、UnslothのVision SFTで扱える会話形式に変換した非公開用データセットです。
各JSONLレコードは「1画像 + 1回答」です。
{
"messages": [
{"role": "user", "content": [
{"type": "image", "image": "images/124469.jpg"},
{"type": "text", "text": "この画像のお題に対して、面白い一言を1つ返してください。"}
]},
{"role": "assistant", "content": [
{"type": "text", "text": "..."}
]}
]
}
Files
train.jsonl: 1,678 records / 630 prompts… See the full description on the dataset page: https://huggingface.co/datasets/beezza/ogiri-bokete-unsloth-vlm.Hermes-OmniForge-Qwen36-27B-full-v0.3.0-unsloth
Hermes OmniForge Qwen3.6-27B Dataset v0.3.0
This package contains the Hermes OmniForge Qwen3.6-27B v0.3.0 synthetic SFT dataset and Unsloth-ready exports.
data/final/train.jsonl
data/final/validation.jsonl
data/final/test.jsonl
data/final/*_unsloth_text.jsonl
data/final/*_unsloth_vision.jsonl
scripts/export_unsloth.py
scripts/validate_dataset.py
scripts/train_unsloth_text_example.py
scripts/train_unsloth_vision_example.py
reports/dataset_report.json
Dataset Shape… See the full description on the dataset page: https://huggingface.co/datasets/r0b0tlab/Hermes-OmniForge-Qwen36-27B-full-v0.3.0-unsloth.unsloth-pmc-vqa-trSupport-Bot-Recommendationstudio_datasetglm53-fidelity-gguf-unsloth-udq4kxl-v1
fidelity--glm53.malaiwah.quant.gguf-unsloth-udq4kxl
A quant fidelity dataset in hidden form, produced by engines/tools/hf_capture.py from unsloth/GLM-5.3-GGUF.
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 after it).… See the full description on the dataset page: https://huggingface.co/datasets/malaiwah/glm53-fidelity-gguf-unsloth-udq4kxl-v1.PrimeVul_For_unsloth_V1.0_failed_finetuningglm52-fidelity-gguf-unsloth-udq4kxl-v1
fidelity--glm52.malaiwah.quant.gguf-unsloth-udq4kxl
A quant fidelity dataset in hidden form, produced by engines/tools/hf_capture.py from unsloth/GLM-5.2-GGUF.
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 after it).… See the full description on the dataset page: https://huggingface.co/datasets/malaiwah/glm52-fidelity-gguf-unsloth-udq4kxl-v1.RealMythosReasoning-unsloth-studio-fixedThe exactly same dataset as RealMythosReasoning(https://huggingface.co/datasets/RealMythos/RealMythosReasoning) but fixed for unsloth studio. Tested on cli and gui, it does work perfectly fine.
dockerNLcommands-sft-unsloth
Docker NL Commands (Unsloth-ready)
Converted from dockerNLcommands-sft-jsonl for Unsloth Studio.
Configurations
Config
Format
Columns
Train rows
Test rows
alpaca (default)
Alpaca
instruction, input, output
2294
121
chatml
ChatML
messages (with role + content)
2294
121
Usage
Unsloth Studio
Dataset → Hugging Face → lakhera2023/dockerNLcommands-sft-unsloth
Format: alpaca (default config)
Train split: train, eval split: test… See the full description on the dataset page: https://huggingface.co/datasets/lakhera2023/dockerNLcommands-sft-unsloth.precompiled_llama_cppsonthenguyen__ft-unsloth-zephyr-sft-bnb-4bit-20241014-170522-details
Dataset Card for Evaluation run of sonthenguyen/ft-unsloth-zephyr-sft-bnb-4bit-20241014-170522
Dataset automatically created during the evaluation run of model sonthenguyen/ft-unsloth-zephyr-sft-bnb-4bit-20241014-170522
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/sonthenguyen__ft-unsloth-zephyr-sft-bnb-4bit-20241014-170522-details.lama3_khg_unsloth_datatenderdataset_unsloth
Dataset Card for Tender Categorization Dataset
Dataset Description
The Tender Categorization Dataset is designed for categorizing various types of tenders into predefined categories. The dataset includes a diverse set of tender descriptions from different domains, and each entry is categorized according to its type. This dataset is useful for training models to automatically classify tenders based on their descriptions.
Data Fields
input: The text description… See the full description on the dataset page: https://huggingface.co/datasets/combatsolutions/tenderdataset_unsloth.details_YeungNLP__firefly-qwen1.5-en-7b-unsloth