# llama2-embedding-1b-8k

Hugging Face: `mesolitica/llama2-embedding-1b-8k`
Reconstructed from `config.json` alone. No weights were read.

| | |
|---|---|
| Derived from structure | 1,071,713,536 |
| In the published checkpoint | 946,902,528 (safetensors.total, 2023-10-10) |
| Delta | +13.2% |
| Comparability | custom-code |
| Layers | 28 |
| Priced on | A10G (24GB) |
| Est. one run | $1812.13 |

> This repository ships its own modeling code (`auto_map`, e.g. `modeling.py`), so `config.json` names a class in the repo rather than an architecture `transformers` defines. The graph below is what those config keys mean under `transformers` semantics, which is not necessarily what the repo's own file builds. A gap here is a statement about what we read, not about the checkpoint.

## Structure

| # | Layer | Type | Output shape |
|---|---|---|---|
| 1 | Input | Input | 1 × 32768 |
| 2 | Embedding | Embedding | 1 × 32768 × 4096 |
| 3 | RoPE | RoPE | 1 × 32768 × 4096 |
| 4 | RMSNorm_1_1 | RMSNorm | 1 × 32768 × 4096 |
| 5 | Attention_1 | Grouped Query Attn | 1 × 32768 × 4096 |
| 6 | Add_1_attn | Add | 1 × 32768 × 4096 |
| 7 | RMSNorm_1_2 | RMSNorm | 1 × 32768 × 4096 |
| 8 | FFN_1 | SwiGLU | 1 × 32768 × 4096 |
| 9 | Add_1_ffn | Add | 1 × 32768 × 4096 |
| 10 | RMSNorm_2_1 | RMSNorm | 1 × 32768 × 4096 |
| 11 | Attention_2 | Grouped Query Attn | 1 × 32768 × 4096 |
| 12 | Add_2_attn | Add | 1 × 32768 × 4096 |
| 13 | RMSNorm_2_2 | RMSNorm | 1 × 32768 × 4096 |
| 14 | FFN_2 | SwiGLU | 1 × 32768 × 4096 |
| 15 | Add_2_ffn | Add | 1 × 32768 × 4096 |
| 16 | RMSNorm_3_1 | RMSNorm | 1 × 32768 × 4096 |
| 17 | Attention_3 | Grouped Query Attn | 1 × 32768 × 4096 |
| 18 | Add_3_attn | Add | 1 × 32768 × 4096 |
| 19 | RMSNorm_3_2 | RMSNorm | 1 × 32768 × 4096 |
| 20 | FFN_3 | SwiGLU | 1 × 32768 × 4096 |
| 21 | Add_3_ffn | Add | 1 × 32768 × 4096 |
| 22 | RMSNorm_4_1 | RMSNorm | 1 × 32768 × 4096 |
| 23 | Attention_4 | Grouped Query Attn | 1 × 32768 × 4096 |
| 24 | Add_4_attn | Add | 1 × 32768 × 4096 |
| 25 | RMSNorm_4_2 | RMSNorm | 1 × 32768 × 4096 |
| 26 | FFN_4 | SwiGLU | 1 × 32768 × 4096 |
| 27 | Add_4_ffn | Add | 1 × 32768 × 4096 |
| 28 | Final_RMSNorm | RMSNorm | 1 × 32768 × 4096 |
| 29 | LM_Head | Linear | 1 × 32768 × 32000 |
| 30 | Output | Output | 1 × 32768 × 32000 |

## Do this to your own model

```
pip install neurarch-trace
neurarch-trace mesolitica/llama2-embedding-1b-8k --plan --share
```

- Page: https://neurarch.com/m/llama2-embedding-1b-8k.html
- All models: https://neurarch.com/m/index.json
- The checks: https://neurarch.com/r/index.json