license, base_model, pipeline_tag, language, tags, library_name, datasets, widget

license	base_model	pipeline_tag	language	tags	library_name	datasets	widget
llama2	meta-llama/Llama-2-7b-hf	text-generation	en	llama text-generation rl-mpq mixed-precision quantization fake-quantization balanced llama-2	transformers	wikitext	text The capital of France is

Llama 2 7B — RL-MPQ Balanced

Standalone RL-MPQ (Reinforcement Learning Mixed-Precision Quantization) checkpoint for the Balanced scenario — a quantized variant of meta-llama/Llama-2-7b-hf.

Field	Value
Base model	meta-llama/Llama-2-7b-hf
Scenario	Balanced
Avg bits / weight	4.375
Compression vs FP16	3.6571×
WikiText-2 PPL	5.0437
Layers	32
Bit distribution	{'4': 29, '8': 3}
Format	Fake-quant FP16 + rlmpq_policy.json

Collection: RL-MPQ — Llama 2 7B — all five scenarios for Llama 2 7B.

Usage

from transformers import AutoModelForCausalLM, AutoTokenizer

repo = "AvoCahDoe/llama-2-7b-rlmpq-balanced"

model = AutoModelForCausalLM.from_pretrained(repo, torch_dtype="float16")
tokenizer = AutoTokenizer.from_pretrained(repo)

Other Llama 2 7B scenarios

Scenario	Avg bits	Compression	WikiText-2 PPL
High Fidelity	6.5	2.4615x	4.9808
Conservative	5.125	3.122x	5.0276
Aggressive	3.5938	4.4522x	5.2614
Extreme Survival	2.9688	5.3895x	10.9577

Grouped archive (all scenarios in one repo): AvoCahDoe/llama-2-7b-rlmpq

Method

1. Phase 3 — PPO agent assigns per-layer bit widths under the Balanced reward target.
2. Phase 4 — Policy replayed on real weights; WikiText-2 perplexity validates quality.
3. Export — Fake-quantized FP16 weights compatible with Hugging Face Transformers.

Files

File	Description
config.json	Llama architecture + RL-MPQ metadata
model.safetensors	Fake-quantized weights
rlmpq_policy.json	Per-layer bit-width policy
rlmpq_metrics.json	Validation & PPL summary

Citation

@misc{rlmpq_llama_2_7b_balanced_2026,
  title  = {RL-MPQ Balanced: Llama 2 7B Mixed-Precision Quantization},
  author = {AvoCahDoe},
  year   = {2026},
  url    = {https://huggingface.co/AvoCahDoe/llama-2-7b-rlmpq-balanced}
}