HuggingFaceTB/smol-smoltalk
Viewer β’ Updated β’ 485k β’ 10.2k β’ 101
This is SFT only checkpoints of karpathy/nanochat-d34, trained using the nanochat framework.
It's same smol-smoltalk which is mentioned in Karpathy OG nanochat discussion
Full details in report/reports.md
| Metric | BASE | MID | SFT | RL |
|---|---|---|---|---|
| ARC-Challenge | - | 0.5367 | 0.5418 | - |
| ARC-Easy | - | 0.6961 | 0.7210 | - |
| GSM8K | - | 0.1137 | 0.1327 | - |
| HumanEval | - | 0.1098 | 0.1037 | - |
| MMLU | - | 0.4229 | 0.4304 | - |
| ChatCORE | - | 0.4045 | 0.4157 | - |
βββ tokenizer/
β βββ tokenizer.pkl # Tokenizer
β βββ token_bytes.pt # Token byte mappings
βββ mid_checkpoints/d34/ # Mid-training checkpoint
β βββ model_*.pt
β βββ meta_*.json
βββ chatsft_checkpoints/d34/ # SFT checkpoint
β βββ model_*.pt
β βββ meta_*.json
βββ chatsft_checkpoints_int8/d34/ # SFT checkpoint
β βββ model_*.pt
β βββ meta_*.json
βββ chatrl_checkpoints/d34/ # RL checkpoint (if available)
β βββ model_*.pt
β βββ meta_*.json
βββ report/ # Evaluation reports
β βββ report.md
βββ logs/ # Training logs
MIT License (same as nanochat)
@misc{nanochat,
author = {Andrej Karpathy},
title = {nanochat: The best ChatGPT that $100 can buy},
year = {2025},
publisher = {GitHub},
url = {https://github.com/karpathy/nanochat}
}
Base model
karpathy/nanochat-d34