---
license: llama3
base_model: meta-llama/Meta-Llama-3-8B
tags:
  - rl-mpq
  - mixed-precision
  - quantization
library_name: transformers
---

# LLAMA-3-8B — Extreme Survival

Subfolder of [`AvoCahDoe/llama-3-8b-rlmpq`](https://huggingface.co/AvoCahDoe/llama-3-8b-rlmpq) (all RL-MPQ scenarios for this model).

Fake-quantized weights for **Extreme_Survival** applied to
[meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) (per-layer asymmetric group-wise quant, group_size=128).

## Load

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

repo = "AvoCahDoe/llama-3-8b-rlmpq"
model = AutoModelForCausalLM.from_pretrained(repo, subfolder="Extreme_Survival", torch_dtype="float16")
tokenizer = AutoTokenizer.from_pretrained(repo, subfolder="Extreme_Survival")
```

## Metrics

| Metric | Value |
|--------|-------|
| Scenario | Extreme_Survival |
| Average bits per weight | 2.875 |
| Compression ratio (vs FP16) | 5.5652x |
| WikiText-2 perplexity | 32.393 |
| Layers | 32 |
| Bit distribution | {'2': 4, '3': 28} |

## Policy (bits per layer)

```
[3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 2, 2]
```

Generated: 2026-06-11T15:42:55.694321