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SynthIQ-7b

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SynthIQ-7b / README.md
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metadata
license: llama2
language:
  - en
tags:
  - mistral
  - merge
library_name: transformers
pipeline_tag: text-generation
base_model:
  - Weyaxi/OpenHermes-2.5-neural-chat-v3-3-openchat-3.5-1210-Slerp
  - uukuguy/speechless-mistral-six-in-one-7b
datasets:
  - stingning/ultrachat
  - garage-bAInd/Open-Platypus
  - Open-Orca/OpenOrca
  - TIGER-Lab/MathInstruct
  - OpenAssistant/oasst_top1_2023-08-25
  - teknium/openhermes
  - meta-math/MetaMathQA
  - Open-Orca/SlimOrca

SynthIQ

SynthIQ

This is SynthIQ, rated 92.23/100 by GPT-4 across varied complex prompts. I used mergekit to merge models.

Benchmark Name Score
ARC 65.87
HellaSwag 85.82
MMLU 64.75
TruthfulQA 57.00
Winogrande 78.69
GSM8K 64.06
AGIEval 42.67
GPT4All 73.71
Bigbench 44.59

Update - 19/01/2024

Tested to work well with autogen and CrewAI

GGUF Files

Q4_K_M - medium, balanced quality - recommended

Q_6_K - very large, extremely low quality loss

Q8_0 - very large, extremely low quality loss - not recommended

Important Update: SynthIQ is now available on Ollama. You can use it by running the command ollama run stuehieyr/synthiq in your terminal. If you have limited computing resources, check out this video to learn how to run it on a Google Colab backend.

Yaml Config 


slices:
  - sources:
      - model: Weyaxi/OpenHermes-2.5-neural-chat-v3-3-openchat-3.5-1210-Slerp
        layer_range: [0, 32]
      - model: uukuguy/speechless-mistral-six-in-one-7b
        layer_range: [0, 32]

merge_method: slerp
base_model: mistralai/Mistral-7B-v0.1

parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5 # fallback for rest of tensors
tokenizer_source: union

dtype: bfloat16

Prompt template: ChatML 

<|im_start|>system
{system_message}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant

License is LLama2 license as uukuguy/speechless-mistral-six-in-one-7b is llama2 license.

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Nous Benchmark Evalation Results

Detailed results can be found here