---
base_model: snorkelai/Snorkel-Mistral-PairRM-DPO
datasets:
- snorkelai/Snorkel-Mistral-PairRM-DPO-Dataset
- HuggingFaceH4/ultrafeedback_binarized
license: apache-2.0
language:
- en
model_creator: snorkelai
model_name: Snorkel-Mistral-PairRM-DPO
model_type: mistral
inference: false
pipeline_tag: text-generation
prompt_template: |
  <|im_start|>system
  {{system_message}}<|im_end|>
  <|im_start|>user
  {{prompt}}<|im_end|>
  <|im_start|>assistant
  
quantized_by: brittlewis12
---

# Snorkel-Mistral-PairRM-DPO GGUF

Original model: [Snorkel-Mistral-PairRM-DPO](https://huggingface.co/snorkelai/Snorkel-Mistral-PairRM-DPO)
Model creator: [Snorkel AI](https://huggingface.co/snorkelai)

This repo contains GGUF format model files for Snorkel AI’s Snorkel-Mistral-PairRM-DPO.

> With this demonstration, we focus on the general approach to alignment. Thus, we use a general-purpose reward model - the performant PairRM model. We use the Mistral-7B-Instruct-v0.2 model as our base LLM.



### What is GGUF?

GGUF is a file format for representing AI models. It is the third version of the format, introduced by the llama.cpp team on August 21st 2023. It is a replacement for GGML, which is no longer supported by llama.cpp.
Converted using llama.cpp b1960 ([26d6076](https://github.com/ggerganov/llama.cpp/commits/26d607608d794efa56df3bdb6043a2f94c1d632c))

### Prompt template: ChatML

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

---

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![cnvrs.ai](https://pbs.twimg.com/profile_images/1744049151241797632/0mIP-P9e_400x400.jpg)

[cnvrs](https://testflight.apple.com/join/sFWReS7K) is the best app for private, local AI on your device:
- create & save **Characters** with custom system prompts & temperature settings
- download and experiment with any **GGUF model** you can [find on HuggingFace](https://huggingface.co/models?library=gguf)!
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---

## Original Model Evaluations:

> On [**Alpaca-Eval 2.0**](https://tatsu-lab.github.io/alpaca_eval/):
> - The base model: [Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) scored **14.72**.
> 
> After applying the above methodology:
> - This model scored **30.22** - ranked 3rd and the highest for an open-source base model at the time of publication.