LMSYS-Chat-1M — LLM Instruction / SFT Dataset
One million real conversations between users and 25 different state-of-the-art LLMs collected from Chatbot Arena. Invaluable for understanding real-world usage patterns, language diversity, and human preferences — spans 154 languages and covers everyday tasks, creative writing, coding, and more.
Dataset Details
| Provider | lmsys |
| Category | Instruction / SFT |
| Size | 1M Conversations |
| License | CC BY-NC 4.0 |
| Downloads | 740k |
| Tags | Real-world, Multi-model, Diverse, 154 Languages, Human Conversations |
from datasets import load_dataset
ds = load_dataset("lmsys/lmsys-chat-1m")
Fine-tune with this dataset
Estimated VRAM to fine-tune with QLoRA (4-bit base model + LoRA adapters), using conservative defaults:
| 7B QLoRA | ~6GB VRAM |
| 13B QLoRA | ~10GB VRAM |
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Related datasets
- WildChat-1M — Training on real user conversations; safety and robustness research
- ShareGPT 52K — Teaching natural multi-turn dialogue (non-commercial)
- Python-Edu — Continued pretraining for Python code understanding
- OpenHermes 2.5 — The default general-purpose SFT mix for 7B-13B fine-tunes
Frequently asked questions
Can I use LMSYS-Chat-1M commercially?
Not in a product — LMSYS-Chat-1M is released under CC BY-NC 4.0, which restricts use to research and other non-commercial purposes. For commercial fine-tuning, pick a permissively licensed dataset from the same category instead.
How much data does LMSYS-Chat-1M contain, and do I need all of it?
LMSYS-Chat-1M contains 1M Conversations. You rarely need all of it: for style and format fine-tuning, a few hundred to a few thousand examples are enough — load a slice (e.g. split="train[:1000]") and scale up only if quality plateaus.
What is LMSYS-Chat-1M best used for?
Studying real-world usage patterns across 25 models (non-commercial). It belongs to the Instruction / SFT section of our dataset hub, where you'll find alternatives and complementary sets.
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