Text Generation
Transformers
Safetensors
English
mistral
Merge
conversational
Eval Results
Inference Endpoints
text-generation-inference
SynthIQ-7b / README.md
sethuiyer's picture
Adding Evaluation Results (#2)
cd98338 verified
---
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|