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smol_llama-220M-GQA
BEE-spoke-data/smol_llama-220M-GQA
smol_llama-220M-GQA is a text generation model from BEE-spoke-data. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as apache-2.0.
A small 220M param (total) decoder model. This is the first version of the model.
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Parameters
218M
436 MB on disk
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13
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At a glance
- Task
- Text Generation
- Library
- transformers
- License
- apache-2.0
- Model type
- llama
- Access
- Public
- Created
- Dec 22, 2023
- Updated
- Dec 29, 2025
- SHA
- 7737e708
Try a prompt
Model card
From the Hugging Face model README
smol_llama: 220M GQA
A small 220M param (total) decoder model. This is the first version of the model.
- 1024 hidden size, 10 layers
- GQA (32 heads, 8 key-value), context length 2048
- train-from-scratch on one GPU :)
Links
Here are some fine-tunes we did, but there are many more possibilities out there!
- instruct
- code
- python (pypi) - link
- zephyr DPO tune
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 29.44 |
| AI2 Reasoning Challenge (25-Shot) | 24.83 |
| HellaSwag (10-Shot) | 29.76 |
| MMLU (5-Shot) | 25.85 |
| TruthfulQA (0-shot) | 44.55 |
| Winogrande (5-shot) | 50.99 |
| GSM8k (5-shot) | 0.68 |
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 6.62 |
| IFEval (0-Shot) | 23.86 |
| BBH (3-Shot) | 3.04 |
| MATH Lvl 5 (4-Shot) | 0.00 |
| GPQA (0-shot) | 0.78 |
| MuSR (0-shot) | 9.07 |
| MMLU-PRO (5-shot) | 1.66 |
- Task
- Text Generation
- Library
- transformers
- Type
- llama
- License
- apache-2.0
- Languages
- en
- Created
- Dec 22, 2023
- Updated
- Dec 29, 2025