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# WestSeverus - 7B - DPO - v2
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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### Recommendations
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## How to Get Started with the Model
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Use the code below to get started with the model.
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[More Information Needed]
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## Training Details
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### Training Data
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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[More Information Needed]
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### Training Procedure
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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#### Preprocessing [optional]
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[More Information Needed]
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#### Training Hyperparameters
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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#### Speeds, Sizes, Times [optional]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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## Evaluation
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<!-- This section describes the evaluation protocols and provides the results. -->
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### Testing Data, Factors & Metrics
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#### Testing Data
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<!-- This should link to a Dataset Card if possible. -->
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[More Information Needed]
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#### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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[More Information Needed]
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#### Metrics
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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[More Information Needed]
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### Results
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[More Information Needed]
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#### Summary
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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## Technical Specifications [optional]
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### Model Architecture and Objective
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[More Information Needed]
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### Compute Infrastructure
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[More Information Needed]
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#### Hardware
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[More Information Needed]
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#### Software
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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## Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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[More Information Needed]
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## More Information [optional]
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## Model Card Authors [optional]
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[More Information Needed]
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## Model Card Contact
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[More Information Needed]
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---
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# WestSeverus - 7B - DPO - v2
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
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## ☘️ Model Description
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WestSeverus-7B-DPO-v2 is a WestLake Family model trained over [WestSeverus-7B](https://huggingface.co/FelixChao/WestSeverus-7B).
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The model was trained on several dpo datasets and it can perform well on basic math problem.
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WestSeverus-7B-DPO-v2 can be used in mathematics, chemical, physics and even coding for further research and reference.
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# 📖 Table of Contents
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1. [Nous Benchmark Results](#🪄-nous-benchmark-results)
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- AGIEval
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- GPT4All
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- TruthfulQA Scores
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- BigBench
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2. [Open LLM Leaderboard](#🏆-open-llm-leaderboard)
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- ARC
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- HellaSwag
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- MMLU
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- TruthfulQA
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- Winogrande
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- GSM8K
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3. [EvalPlus Leaderboard](#⚡-evalplus-leaderboard)
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- HumanEval
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- HumanEval_Plus
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- MBPP
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- MBPP_Plus
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4. [Prompt Format](#prompt-format)
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5. [Inference Example Code](#inference-code)
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6. [Quantized Models](#🛠️-quantized-models)
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7. [Gratitude](#Gratitude)
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## 🪄 Nous Benchmark Results
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WestSeverus-7B-DPO-v2 is currently on the top of the [YALL - Yet Another LLM Leaderboard](https://huggingface.co/spaces/CultriX/Yet_Another_LLM_Leaderboard) created by CultriX and it outperforms on TruthfulQA Scores and BigBench.
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| Model | Average | AGIEval | GPT4All | TruthfulQA | Bigbench |
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|---|---:|---:|---:|---:|---:|
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| [**WestSeverus-7B-DPO-v2**](https://huggingface.co/FelixChao/WestSeverus-7B-DPO-v2)| **60.98**| 45.29 | 77.2| **72.72**| **48.71**|
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| [CultriX/Wernicke-7B-v1](https://huggingface.co/CultriX/Wernicke-7B-v1)| 60.73| 45.59 | 77.36 | 71.46 | 48.49 |
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| [mlabonne/NeuralBeagle14-7B](https://huggingface.co/mlabonne/NeuralBeagle14-7B) | 60.25 |46.06|76.77 | 70.32 |47.86 |
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| [CultriX/MistralTrix-v1](https://huggingface.co/CultriX/MistralTrix-v1) | 60.05 | 44.98 | 76.62 | 71.44 | 47.17 |
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| [senseable/WestLake-7B-v2](https://huggingface.co/senseable/WestLake-7B-v2) | 59.42 | 44.27 | 77.86 | 67.46 | 48.09 |
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| [mlabonne/Daredevil-7B](https://huggingface.co/mlabonne/Daredevil-7B) | 58.22 | 44.85 | 76.07 | 64.89 | 47.07 |
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| [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) | 44.61 | 27.96 | 70.84 | 44.46 | 35.17 |
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## 🏆 Open LLM Leaderboard
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WestSeverus-7B-DPO-v2 is one of the top 7B model in Open LLM Leaderboard and it outperforms on TruthfulQA and GSM8K.
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |75.29|
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|AI2 Reasoning Challenge (25-Shot)|71.42|
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|HellaSwag (10-Shot) |88.27|
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|MMLU (5-Shot) |64.79|
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|TruthfulQA (0-shot) |72.37|
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|Winogrande (5-shot) |83.27|
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|GSM8k (5-shot) |71.65|
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_FelixChao__WestSeverus-7B-DPO-v2)
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## ⚡ EvalPlus Leaderboard
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| Model | HumanEval | HumanEval_Plus| MBPP | MBPP_Plus |
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|---|---:|---:|---:|---:|
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| phi-2-2.7B |48.2|43.3|61.9|51.4|
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| **WestSeverus-7B-DPO-v2**| 43.3 | 34.1 |TBD |TBD |
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| SOLAR-10.7B-Instruct-v1.0 | 42.1 | 34.3 | 42.9 | 34.6 |
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| CodeLlama-7B| 37.8| 34.1 | 57.6 |45.4 |
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
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## Prompt_Format
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TBD.
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## Inference Example Code
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TBD.
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## 🛠️ Quantized Models
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### Another version of WestSeverus Model:
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* [**PetroGPT/WestSeverus-7B-DPO**](https://huggingface.co/PetroGPT/WestSeverus-7B-DPO)
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* **GGUF**: https://huggingface.co/TheBloke/WestSeverus-7B-DPO-GGUF
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* **GGUF**: https://huggingface.co/s3nh/WestSeverus-7B-DPO-GGUF
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* **GPTQ**: https://huggingface.co/TheBloke/WestSeverus-7B-DPO-GPTQ
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* **AWQ**: https://huggingface.co/TheBloke/WestSeverus-7B-DPO-AWQ
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## Gratitude
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TBD.
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