🚧"raw" pretrained smol_llama checkpoints - WIP 🚧 • 4 items • Updated • 6
smol_llama-81M-tied
👁 bannerA small 81M param (total) decoder model, enabled through tying the input/output embeddings. This is the first version of the model.
- 768 hidden size, 6 layers
- standard multi-head attention (24 heads), context length 1024
- input/output embeddings are tied
- train-from-scratch
Notes
This checkpoint is the 'raw' pre-trained model and has not been tuned to a more specific task. It should be fine-tuned before use in most cases.
- slightly larger 101M param GQA pretrained version: here
- For the chat version of this model, please see here
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 24.52 |
| ARC (25-shot) | 22.18 |
| HellaSwag (10-shot) | 29.33 |
| MMLU (5-shot) | 24.06 |
| TruthfulQA (0-shot) | 43.97 |
| Winogrande (5-shot) | 49.25 |
| GSM8K (5-shot) | 0.23 |
| DROP (3-shot) | 2.64 |
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Safetensors
Model size
81.3M params
Tensor type
F32
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