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
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
- 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:
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, 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