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## Solar-10.7B-SLERP-EXL2
Model: [Solar-10.7B-SLERP](https://huggingface.co/jan-hq/Solar-10.7B-SLERP)  
Made by: [jan-hq](https://huggingface.co/jan-hq)  

Based on original model: [SOLAR-10.7B-Instruct-v1.0](https://huggingface.co/upstage/SOLAR-10.7B-Instruct-v1.0)  
Created by: [upstage](https://huggingface.co/upstage)  

## List of quants:
[4bpw h8 (main)](https://huggingface.co/cgus/Solar-10.7B-SLERP-exl2/tree/main)  
[4.65bpw h8](https://huggingface.co/cgus/Solar-10.7B-SLERP-exl2/tree/4.65bpw-h8)  
[5bpw h8](https://huggingface.co/cgus/Solar-10.7B-SLERP-exl2/tree/5bpw-h8)  
[6bpw h8](https://huggingface.co/cgus/Solar-10.7B-SLERP-exl2/tree/6bpw-h8)  
[8bpw h8](https://huggingface.co/cgus/Solar-10.7B-SLERP-exl2/tree/8bpw-h8)  

## Quantization notes

30.01.2024 Replaced old quants with newer ones that were made with exllamav2-0.0.12, calibrated with default exllamav2 dataset.  
This model uses a lot less memory compared to Llama2-13B models and it *almost* fits 12GB VRAM even at 8bpw.  
But with 8-bit cache it even uses just a tiny bit less than 12GB VRAM.  

## How to run

This quantization method uses GPU and requires Exllamav2 loader which can be found in following applications:

[Text Generation Webui](https://github.com/oobabooga/text-generation-webui)  

[KoboldAI](https://github.com/henk717/KoboldAI)  

[ExUI](https://github.com/turboderp/exui)  
  
# Original model card:

<div style="width: auto; margin-left: auto; margin-right: auto">
<img src="https://github.com/janhq/jan/assets/89722390/35daac7d-b895-487c-a6ac-6663daaad78e" alt="Jan banner" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</div>

<p align="center">
    <a href="https://jan.ai/">Jan</a
> 
    - <a href="https://discord.gg/AsJ8krTT3N">Discord</a>
</p>
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# Model Description
This model uses the `Slerp` merge method from the best models on 14th Dec on the [OpenLLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard):
1. [upstage/SOLAR-10.7B-Instruct-v1.0](https://huggingface.co/upstage/SOLAR-10.7B-Instruct-v1.0)
2. [janhq/Pandora-v1-10.7B](https://huggingface.co/janhq/Pandora-v1-10.7B)

- base model: [upstage/SOLAR-10.7B-Instruct-v1.0](https://huggingface.co/upstage/SOLAR-10.7B-Instruct-v1.0)

The yaml config file for this model is here:

```yaml
slices:
  - sources:
      - model: upstage/SOLAR-10.7B-Instruct-v1.0
        layer_range: [0, 48]
      - model: janhq/Pandora-v1-10.7B
        layer_range: [0, 48]
merge_method: slerp
base_model: upstage/SOLAR-10.7B-Instruct-v1.0
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
dtype: bfloat16
```

# Prompt template

- **ChatML**

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

# Run this model
You can run this model using [Jan Desktop](https://jan.ai/) 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 `1337` with OpenAI compatible endpoints
- 🌍 **Open Source & Free**: We build in public; check out our [Github](https://github.com/janhq)

![image/png](https://cdn-uploads.huggingface.co/production/uploads/65713d70f56f9538679e5a56/r7VmEBLGXpPLTu2MImM7S.png)

# 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
- [mergekit](https://github.com/cg123/mergekit)
- [DARE](https://github.com/yule-BUAA/MergeLM/blob/main/README.md)
- [SLERP](https://github.com/Digitous/LLM-SLERP-Merge)
- [lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness)
{"language": ["en"], "license": "apache-2.0", "inference": false}
transformers llama text-generation conversational en license:apache-2.0 autotrain_compatible text-generation-inference region:us