108 lines
3.0 KiB
Markdown
108 lines
3.0 KiB
Markdown
---
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license: cc-by-nc-4.0
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language:
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- en
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pipeline_tag: text-generation
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---
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Merge:
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```
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slices:
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- sources:
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- model: viethq188/LeoScorpius-7B-Chat-DPO
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layer_range: [0, 32]
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- model: GreenNode/GreenNodeLM-7B-v1olet
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layer_range: [0, 32]
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merge_method: slerp
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base_model: viethq188/LeoScorpius-7B-Chat-DPO
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parameters:
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t:
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- filter: self_attn
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value: [0, 0.5, 0.3, 0.7, 1]
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- filter: mlp
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value: [1, 0.5, 0.7, 0.3, 0]
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- value: 0.5 # fallback for rest of tensors
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dtype: float16
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```
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# Go Bruins V2.1 - A Fine-tuned Language Model
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## Updates
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## Overview
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**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.
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## Model Details
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- **Developer:** Ryan Witzman
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- **Base Model:** [rwitz/go-bruins](https://huggingface.co/rwitz/go-bruins)
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- **Fine-tuning Method:** Direct Preference Optimization (DPO)
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- **Training Steps:** 642
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- **Language:** English
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- **License:** MIT
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## Capabilities
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Go Bruins excels in a variety of NLP tasks, including but not limited to:
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- Text generation
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- Language understanding
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- Sentiment analysis
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## Usage
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**Warning:** This model may output NSFW or illegal content. Use with caution and at your own risk.
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### For Direct Use:
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```python
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from transformers import pipeline
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model_name = "rwitz/go-bruins-v2"
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inference_pipeline = pipeline('text-generation', model=model_name)
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input_text = "Your input text goes here"
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output = inference_pipeline(input_text)
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print(output)
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```
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### Not Recommended For:
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- Illegal activities
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- Harassment
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- Professional advice or crisis situations
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## Training and Evaluation
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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.
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# Evaluations
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| Metric | Average | Arc Challenge | Hella Swag | MMLU | Truthful Q&A | Winogrande | GSM8k |
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|---------------|---------|---------------|------------|------|--------------|------------|-------|
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| **Score** | 72.07 | 69.8 | 87.05| 64.75 | 59.7 | 81.45 | 69.67 |
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Note: The original MMLU evaluation has been corrected to include 5-shot data rather than 1-shot data.
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## Contact
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For any inquiries or feedback, reach out to Ryan Witzman on Discord: `rwitz_`.
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---
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## Citations
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```
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@misc{unacybertron7b,
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title={Cybertron: Uniform Neural Alignment},
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author={Xavier Murias},
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year={2023},
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publisher = {HuggingFace},
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journal = {HuggingFace repository},
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howpublished = {\url{https://huggingface.co/fblgit/una-cybertron-7b-v2-bf16}},
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}
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```
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*This model card was created with care by Ryan Witzman.*
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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 |