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pankajmathur/nanochat-d34-sft
nanochat-d34-sft is a text generation model from pankajmathur. Use it when you need the model to write or continue text. The card lists the license as mit.
This is SFT only checkpoints of karpathy/nanochat-d34, trained using the nanochat framework.
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Updated Dec 9, 2025
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From the Hugging Face model README
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 | - |
├── tokenizer/
│ ├── tokenizer.pkl # Tokenizer
│ └── token_bytes.pt # Token byte mappings
├── mid_checkpoints/d34/ # Mid-training checkpoint
│ ├── model_*.pt
│ └── meta_*.json
├── chatsft_checkpoints/d34/ # SFT checkpoint
│ ├── model_*.pt
│ └── meta_*.json
├── chatsft_checkpoints_int8/d34/ # SFT checkpoint
│ ├── model_*.pt
│ └── meta_*.json
├── chatrl_checkpoints/d34/ # RL checkpoint (if available)
│ ├── model_*.pt
│ └── meta_*.json
├── report/ # Evaluation reports
│ └── report.md
└── 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}
}