Model Description
This model uses the DARE method to merge Mistral-7B-Instruct-v0.2 with 3 leading models in 12th Dec on OpenLLM Leaderboard:
- OpenHermes-2.5-neural-chat-v3-3-Slerp
- MetaMath-Cybertron-Starling
- v1olet_marcoroni-go-bruins-merge-7B
- base model: Mistral-7B-Instruct-v0.2
The yaml config file for this model is here:
base_model: mistralai/Mistral-7B-Instruct-v0.2
dtype: bfloat16
merge_method: dare_ties
models:
- model: mistralai/Mistral-7B-Instruct-v0.2
- model: Weyaxi/OpenHermes-2.5-neural-chat-v3-3-Slerp
parameters:
density: 0.8
weight: 0.4
- model: Q-bert/MetaMath-Cybertron-Starling
parameters:
density: 0.8
weight: 0.3
- model: v1olet/v1olet_marcoroni-go-bruins-merge-7B
parameters:
density: 0.8
weight: 0.3
parameters:
int8_mask: true
Prompt template:
- ChatML
<|im_start|>system
{system_message}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
- Alpaca
{system_message}
### Instruction:
{prompt}
### Response:
Run this model
You can run this model using Jan Desktop on Mac, Windows, or Linux.
Jan is an open source, ChatGPT alternative that is:
- 💻 100% offline on your machine: Your conversations remain confidential, and visible only to you.
- 🗂️ An Open File Format: Conversations and model settings stay on your computer and can be exported or deleted at any time.
- 🌐 OpenAI Compatible: Local server on port
1337with OpenAI compatible endpoints - 🌍 Open Source & Free: We build in public; check out our Github
About Jan
Jan believes in the need for an open-source AI ecosystem and is building the infra and tooling to allow open-source AIs to compete on a level playing field with proprietary ones.
Jan's long-term vision is to build a cognitive framework for future robots, who are practical, useful assistants for humans and businesses in everyday life.
Jan Model Merger
This is a test project for merging models.
Open LLM Leaderboard Evaluation Results
Detailed results can be found here.
| Metric | Value |
|---|---|
| Avg. | ? |
| ARC (25-shot) | ? |
| HellaSwag (10-shot) | ? |
| MMLU (5-shot) | ? |
| TruthfulQA (0-shot) | ? |
| Winogrande (5-shot) | ? |
| GSM8K (5-shot) | ? |
Acknowlegement
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 55.84 |
| AI2 Reasoning Challenge (25-Shot) | 61.95 |
| HellaSwag (10-Shot) | 75.62 |
| MMLU (5-Shot) | 49.99 |
| TruthfulQA (0-shot) | 54.36 |
| Winogrande (5-shot) | 74.98 |
| GSM8k (5-shot) | 18.12 |