README.md

metadata

license: cc-by-nc-4.0

Re:MythoMax (ReMM) is a recreation trial of the original MythoMax-L2-B13 with updated models.

This merge use SLERP [TESTING] to merge ReML and Huginn v1.2.

Command useds and explaination :

Due to hardware limitation, some merge was done in 2 part.

- Recreate ReML : Mythologic (v2) (Chronos/Hermes/Airboros)
=> Replacing Chronos by The-Face-Of-Goonery/Chronos-Beluga-v2-13bfp16 (0.30)
=> Replacing Airoboros by jondurbin/airoboros-l2-13b-2.1 (last version) (0.40)
=> Keeping NousResearch/Nous-Hermes-Llama2-13b (0.30)

Part 1: python ties_merge.py TheBloke/Llama-2-13B-fp16 ./ReML-L2-13B-part1  --merge The-Face-Of-Goonery/Chronos-Beluga-v2-13bfp16 --density 0.42 --merge jondurbin/airoboros-l2-13b-2.1 --density 0.56 --cuda

Part 2: python ties_merge.py TheBloke/Llama-2-13B-fp16 ./ReML-L2-13B --merge NousResearch/Nous-Hermes-Llama2-13b --density 0.30 --merge Undi95/ReML-L2-13B-part1 --density 0.70 --cuda

With that :
- Recreate ReMM : MythoMax (v2) (Mythologic/Huginn v1)
=> Replacing Mythologic by the one above (0.5)
=> Replacing Huginn by The-Face-Of-Goonery/Huginn-13b-v1.2 (hottest) (0.5)

Part 3: python slerpmergelm.py "The-Face-Of-Goonery_Huginn-13b-v1.2" "Undi95_ReML-L2-13B" "result"

Version of SLERP used is different to accept usage on notebook : https://github.com/Undi95/LLM-SLERP-MergeTest/tree/main (Thanks @Vali)

Description

This repo contains fp16 files of ReMM-SLERP, a recreation of the original MythoMax, but updated and merged with SLERP.

Models used

• TheBloke/Llama-2-13B-fp16 (base)
• The-Face-Of-Goonery/Chronos-Beluga-v2-13bfp16
• jondurbin/airoboros-l2-13b-2.1
• NousResearch/Nous-Hermes-Llama2-13b
• The-Face-Of-Goonery/Huginn-13b-v1.2
• ReML-L2-13B (Private recreation trial of an updated Mythologic-L2-13B)

Prompt template: Alpaca

Below is an instruction that describes a task. Write a response that appropriately completes the request.

### Instruction:
{prompt}

### Response:

Special thanks to Sushi kek

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	50.99
ARC (25-shot)	60.92
HellaSwag (10-shot)	83.56
MMLU (5-shot)	55.33
TruthfulQA (0-shot)	51.97
Winogrande (5-shot)	75.22
GSM8K (5-shot)	9.17
DROP (3-shot)	20.76