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--- |
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language: |
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- en |
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license: cc-by-nc-4.0 |
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datasets: |
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- Intel/orca_dpo_pairs |
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pipeline_tag: text-generation |
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model-index: |
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- name: go-bruins |
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results: |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: AI2 Reasoning Challenge (25-Shot) |
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type: ai2_arc |
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config: ARC-Challenge |
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split: test |
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args: |
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num_few_shot: 25 |
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metrics: |
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- type: acc_norm |
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value: 69.11 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rwitz/go-bruins |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: HellaSwag (10-Shot) |
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type: hellaswag |
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split: validation |
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args: |
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num_few_shot: 10 |
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metrics: |
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- type: acc_norm |
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value: 86.73 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rwitz/go-bruins |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MMLU (5-Shot) |
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type: cais/mmlu |
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config: all |
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split: test |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 64.94 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rwitz/go-bruins |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: TruthfulQA (0-shot) |
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type: truthful_qa |
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config: multiple_choice |
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split: validation |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: mc2 |
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value: 58.71 |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rwitz/go-bruins |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: Winogrande (5-shot) |
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type: winogrande |
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config: winogrande_xl |
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split: validation |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 81.45 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rwitz/go-bruins |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: GSM8k (5-shot) |
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type: gsm8k |
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config: main |
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split: test |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 69.9 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rwitz/go-bruins |
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name: Open LLM Leaderboard |
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--- |
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/63a259d0f30c46422789d38d/vO3iATjO8ulfcakTltE4k.png) |
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# Go Bruins - A Fine-tuned Language Model |
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Join my AI Discord: [rwitz](https://discord.gg/qbqjBEfkGw) |
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## Updates |
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December 9, 2023: |
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Go-Bruins has placed **#6** overall and **#1** for 7 billion parameter models on the [Hugging Face Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)! |
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## Overview |
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**Go Bruins** is a state-of-the-art language model fine-tuned on the Q-bert/MetaMath-Cybertron-Starling 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:** [Q-bert/MetaMath-Cybertron-Starling](https://huggingface.co/Q-bert/MetaMath-Cybertron-Starling) |
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- **Fine-tuning Method:** Direct Preference Optimization (DPO) |
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- **Training Steps:** 200 |
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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" |
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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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GGUF Quantized Files are Located at [NyxKrage/go-bruins-GGUF](https://huggingface.co/NyxKrage/go-bruins-GGUF) |
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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 [Intel/orca_dpo_pairs](https://huggingface.co/datasets/Intel/orca_dpo_pairs), Go Bruins has shown promising improvements over its predecessor, Q-Bert. |
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# Evaluations |
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Go-Bruins is the SOTA 7B model. |
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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** | 71.86 | 69.11 | 86.53| 65.02 | 59.24 | 81.37 | 69.90 | |
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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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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) |
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_rwitz__go-bruins) |
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| Metric |Value| |
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|---------------------------------|----:| |
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|Avg. |71.81| |
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|AI2 Reasoning Challenge (25-Shot)|69.11| |
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|HellaSwag (10-Shot) |86.73| |
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|MMLU (5-Shot) |64.94| |
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|TruthfulQA (0-shot) |58.71| |
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|Winogrande (5-shot) |81.45| |
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|GSM8k (5-shot) |69.90| |
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