datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
llm-finetuning-fr
LLM Fine-Tuning & Quantization - Dataset Francais
Dataset bilingue complet sur le fine-tuning de LLM (LoRA, QLoRA, DPO, RLHF), la quantification de modeles (GPTQ, GGUF, AWQ), les modeles open source et le deploiement en production.
Description
Ce dataset couvre l'ensemble de la chaine de valeur des LLM open source, du fine-tuning au deploiement en production. Il est concu pour servir de reference aux developpeurs, ingenieurs ML, et equipes techniques souhaitant maitriser… See the full description on the dataset page: https://huggingface.co/datasets/AYI-NEDJIMI/llm-finetuning-fr.High-Quality-Synthetic-Python-Dataset-with-Reasoning-Traces-Chain-of-Thought-for-LLM-Fine-Tuning
PyReason-7k: Advanced Python Chain-of-Thought Dataset
Dataset Description
This dataset contains 7,000+ high-quality Python programming examples designed for LLM fine-tuning.
Each entry includes a detailed thought_process (Chain-of-Thought) to teach models logical reasoning before coding.
Key Features:
Chain-of-Thought: Step-by-step reasoning traces.
Error Handling: Solutions include try-except blocks and logging.
Diverse Tasks: Algorithms, API handling, Data Structures.… See the full description on the dataset page: https://huggingface.co/datasets/xTayyub/High-Quality-Synthetic-Python-Dataset-with-Reasoning-Traces-Chain-of-Thought-for-LLM-Fine-Tuning.llm-finetuning-en
LLM Fine-Tuning & Quantization - English Dataset
Comprehensive bilingual dataset on LLM fine-tuning (LoRA, QLoRA, DPO, RLHF), model quantization (GPTQ, GGUF, AWQ), open source models, and production deployment.
Description
This dataset covers the entire open source LLM value chain, from fine-tuning to production deployment. It is designed as a reference for developers, ML engineers, and technical teams looking to master open source LLMs.
Dataset Content… See the full description on the dataset page: https://huggingface.co/datasets/AYI-NEDJIMI/llm-finetuning-en.LLM_FineTuning_Dataset_13M
Merged LLM Instruction Datasets (13M Samples)
This dataset is a large-scale merge of high-quality instruction-tuning datasets commonly used for fine-tuning large language models (LLMs). It combines samples from multiple sources into a single, unified JSONL file format, optimized for streaming and efficient training. The merge prioritizes valid, parseable samples while skipping invalid ones (e.g., due to JSON errors) and large files that exceed processing limits.
The final merged… See the full description on the dataset page: https://huggingface.co/datasets/1Manu/LLM_FineTuning_Dataset_13M.