go-bruins-v2.1 / README.md
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---
license: cc-by-nc-4.0
language:
- en
pipeline_tag: text-generation
---
Merge:
```
slices:
- sources:
- model: viethq188/LeoScorpius-7B-Chat-DPO
layer_range: [0, 32]
- model: GreenNode/GreenNodeLM-7B-v1olet
layer_range: [0, 32]
merge_method: slerp
base_model: viethq188/LeoScorpius-7B-Chat-DPO
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
dtype: float16
```
![image/png](https://cdn-uploads.huggingface.co/production/uploads/63a259d0f30c46422789d38d/tmdM1fjNAmzV125zWd3_J.png)
# Go Bruins V2.1 - A Fine-tuned Language Model
## Updates
## Overview
**Go Bruins-V2** is a language model fine-tuned on the rwitz/go-bruins architecture. It's designed to push the boundaries of NLP applications, offering unparalleled performance in generating human-like text.
## Model Details
- **Developer:** Ryan Witzman
- **Base Model:** [rwitz/go-bruins](https://huggingface.co/rwitz/go-bruins)
- **Fine-tuning Method:** Direct Preference Optimization (DPO)
- **Training Steps:** 642
- **Language:** English
- **License:** MIT
## Capabilities
Go Bruins excels in a variety of NLP tasks, including but not limited to:
- Text generation
- Language understanding
- Sentiment analysis
## Usage
**Warning:** This model may output NSFW or illegal content. Use with caution and at your own risk.
### For Direct Use:
```python
from transformers import pipeline
model_name = "rwitz/go-bruins-v2"
inference_pipeline = pipeline('text-generation', model=model_name)
input_text = "Your input text goes here"
output = inference_pipeline(input_text)
print(output)
```
### Not Recommended For:
- Illegal activities
- Harassment
- Professional advice or crisis situations
## Training and Evaluation
Trained on a dataset from [athirdpath/DPO_Pairs-Roleplay-Alpaca-NSFW](https://huggingface.co/datasets/athirdpath/DPO_Pairs-Roleplay-Alpaca-NSFW), Go Bruins V2 has shown promising improvements over its predecessor, Go Bruins.
# Evaluations
| Metric | Average | Arc Challenge | Hella Swag | MMLU | Truthful Q&A | Winogrande | GSM8k |
|---------------|---------|---------------|------------|------|--------------|------------|-------|
| **Score** | 72.07 | 69.8 | 87.05| 64.75 | 59.7 | 81.45 | 69.67 |
Note: The original MMLU evaluation has been corrected to include 5-shot data rather than 1-shot data.
## Contact
For any inquiries or feedback, reach out to Ryan Witzman on Discord: `rwitz_`.
---
## Citations
```
@misc{unacybertron7b,
title={Cybertron: Uniform Neural Alignment},
author={Xavier Murias},
year={2023},
publisher = {HuggingFace},
journal = {HuggingFace repository},
howpublished = {\url{https://huggingface.co/fblgit/una-cybertron-7b-v2-bf16}},
}
```
*This model card was created with care by Ryan Witzman.*
rewrite this model card for new version called go-bruins-v2 that is finetuned on dpo on the original go-bruins model on athirdpath/DPO_Pairs-Roleplay-Alpaca-NSFW