README.md

---
language:
- en
license: llama2
library_name: transformers
tags:
- mistral
- merge
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
pipeline_tag: text-generation
base_model:
- Weyaxi/OpenHermes-2.5-neural-chat-v3-3-openchat-3.5-1210-Slerp
- ehartford/dolphin-2.1-mistral-7b
- Open-Orca/Mistral-7B-OpenOrca
- bhenrym14/mistral-7b-platypus-fp16
- ehartford/samantha-1.2-mistral-7b
- iteknium/CollectiveCognition-v1.1-Mistral-7B
- HuggingFaceH4/zephyr-7b-alpha
model-index:
- name: sethuiyer/SynthIQ-7b
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: AI2 Reasoning Challenge (25-Shot)
      type: ai2_arc
      config: ARC-Challenge
      split: test
      args:
        num_few_shot: 25
    metrics:
    - type: acc_norm
      value: 65.87
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=sethuiyer/SynthIQ-7b
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: HellaSwag (10-Shot)
      type: hellaswag
      split: validation
      args:
        num_few_shot: 10
    metrics:
    - type: acc_norm
      value: 85.82
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=sethuiyer/SynthIQ-7b
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MMLU (5-Shot)
      type: cais/mmlu
      config: all
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 64.75
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=sethuiyer/SynthIQ-7b
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: TruthfulQA (0-shot)
      type: truthful_qa
      config: multiple_choice
      split: validation
      args:
        num_few_shot: 0
    metrics:
    - type: mc2
      value: 57
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=sethuiyer/SynthIQ-7b
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: Winogrande (5-shot)
      type: winogrande
      config: winogrande_xl
      split: validation
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 78.69
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=sethuiyer/SynthIQ-7b
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GSM8k (5-shot)
      type: gsm8k
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 64.06
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=sethuiyer/SynthIQ-7b
      name: Open LLM Leaderboard
---

<p align="center">
  <img src="https://codeberg.org/aninokuma/DeydooAssistant/raw/branch/main/logo.webp" height="256px" alt="SynthIQ">
</p>

# SynthIQ

This is SynthIQ, rated **92.23/100** by GPT-4 across varied complex prompts. I used [mergekit](https://github.com/cg123/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](https://huggingface.co/sethuiyer/SynthIQ_GGUF/blob/main/synthiq.Q4_K_M.gguf) - medium, balanced quality - recommended

[Q_6_K](https://huggingface.co/sethuiyer/SynthIQ_GGUF/blob/main/synthiq.Q6_K.gguf) - very large, extremely low quality loss

[Q8_0](https://huggingface.co/sethuiyer/SynthIQ_GGUF/blob/main/synthiq.Q8.gguf) - 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](https://www.youtube.com/watch?v=Qa1h7ygwQq8) to learn how to run it on 
a Google Colab backend.


# Yaml Config

```yaml

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 start -->
## Prompt template: ChatML

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

```

<!-- prompt-template end -->


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

# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_sethuiyer__SynthIQ-7b)

# [Nous Benchmark Evalation Results](https://huggingface.co/spaces/mlabonne/Yet_Another_LLM_Leaderboard)
Detailed results can be found [here](https://gist.github.com/sethuiyer/f47dee388a4e95d46181c98d37d66a58)
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_sethuiyer__SynthIQ-7b)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |69.37|
|AI2 Reasoning Challenge (25-Shot)|65.87|
|HellaSwag (10-Shot)              |85.82|
|MMLU (5-Shot)                    |64.75|
|TruthfulQA (0-shot)              |57.00|
|Winogrande (5-shot)              |78.69|
|GSM8k (5-shot)                   |64.06|