---
base_model: HuggingFaceH4/zephyr-orpo-141b-A35b-v0.1
license: apache-2.0
---

# Importance-Matrix quantizations of HuggingFaceH4/zephyr-orpo-141b-A35b-v0.1 
# first mixtral8x22b finetune 💫

This is a handrolled quantization off of a custom but backwards compatible fork of llama.cpp 
Hoping to push edgequants to main llama.cpp repo soon

## MAKE SURE TO MERGE TOGETHER THE TWO PARTS AFTER DOWNLOADING
## I.e. Download the 3bit orpo4ns.gguf.part0 & orpo4ns.gguf.part1 files then:
``` 
cd ~/Downloads

cat orpo4ns.gguf.part* > orpo4ns.gguf

cd llamacppFolderLocaltion 

./server -m ~/Downloads/orpor4ns.gguf -ngl 56 
```
careful this can take 5 minutes or up to 10-15 on slow instances, check progress with ls -la

For lmStudio you need to copy the full orpo3ns.gguf file to your ~/.cache/lm-studio/models/YourNAME/ 

## orpo4ns.gguf is the fastest, recommended, 2bit also done but not recommended.

the imatrix.dat file was calcuated over 1000 chunks with wikitext.train.raw( included )

Wrote a bit of custom c++ to avoid quantizing certain layers, tested fully compatible with llama.cpp as of 10April2024.

I'm no longer using the gguf-split tensor sharding because the memory swapping slows down GPU inference a lot.

# Run with llama.cpp 

```
git clone https://github.com/ggerganov/llama.cpp && cd llama.cpp/ && make -j

./main -m orpo4ns.gguf -n 256 -t 64 --temp 0.2 --color -p "How to build a city on mars via aldrin cycler orbit shipments?"

```
# Perplexity benchmarks

Command I used to run these on 48 core CPU only machine, you can add -ngl 16 to offload 16 layers or more to gpu on your own.

```./perplexity -m orpo4ns.gguf -f wiki.test.raw --chunks 12 -t 48 ``` 

# Lower is Better. F16 baseline is ~2.3 , the 3bit 58GB version however is surprisingly not far
# orpor4ns.gguf is the fastest because of 4bit/8bit optimizations in most hardware.

```bash
orpor4ns.gguf FILESIZE: 71260 MB 
[1]2.6970,[2]3.1781,[3]3.7390,[4]3.4159,[5]2.8977,[6]2.7126,[7]2.5597,[8]2.5013,[9]2.5279,[10]2.5175,[11]2.5315,[12]2.5455,
Final estimate: PPL = 2.5455 +/- 0.07697

orpo3ns.gguf FILESIZE: 58536 MB
[1]2.8042,[2]3.3418,[3]3.9400,[4]3.5859,[5]3.2042,[6]3.0524,[7]2.9738,[8]2.9695,[9]3.0232,[10]3.0099,[11]3.0510,[12]3.0589,
Final estimate: PPL = 3.0589 +/- 0.09882

orpo3nm.gguf FILESIZE: 60828 MB
[1]2.8435,[2]3.2998,[3]3.8984,[4]3.4821,[5]3.1084,[6]2.9597,[7]2.8[9]2.9155,[10]2.9218,[11]2.9613,[12]2.9709,
Final estimate: PPL = 2.9709 +/- 0.09419

orpo3nl.gguf FILESIZE: 65405 MB
[1]2.8175,[2]3.2506,[3]3.8241,[4]3.4152,[5]2.9970,[6]2.8455,[7]2.7358,[8]2.7120,[9]2.7955,[10]2.8003,[11]2.8254,[12]2.8371,
Final estimate: PPL = 2.8371 +/- 0.08781

orpo2n.gguf FILESIZE: 49420 MB
[1]3.0082,[2]3.5829,[3]4.1414,[4]4.1671,[5]3.8567,[6]3.7209,[7]3.7150,[8]3.7210,[9]3.8445,[10]3.9332,[11]4.0879,[12]4.0884,
Final estimate: PPL = 4.0884 +/- 0.1499

orpo2ns.gguf FILESIZE: 44026 MB
[1]3.0077,[2]3.5575,[3]4.1028,[4]4.4088,[5]4.2206,[6]4.1056,[7]4.1029,[8]4.1305,[9]4.1791,[10]4.3247,[11]4.4759,[12]4.4659,
Final estimate: PPL = 4.4659 +/- 0.16582
```
People on twitter seem very happy with 4bit version. Getting 3x higher speeds(13.01tps on an M3 Max macbook) than 4bit MLX(4.5tps)
![image/png](https://cdn-uploads.huggingface.co/production/uploads/6379683a81c1783a4a2ddba8/id32eagz3KNxiK3NC6cTv.png)


# The 3bit version is surprisingly usable even though only 58GB. Use 3ns or 3nm if you have a 64gb mac.