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README.md
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/657e900beaad53ff67ba84db/uPWIuw_wAOwRk9O8qlZxZ.png)
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## Model
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<!-- Provide a longer summary of what this model is. -->
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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### Downstream Use [optional]
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[More Information Needed]
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### Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further 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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[More Information Needed]
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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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[More Information Needed]
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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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[More Information Needed]
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## Model Card Authors [optional]
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## Model Card Contact
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[More Information Needed]
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/657e900beaad53ff67ba84db/uPWIuw_wAOwRk9O8qlZxZ.png)
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## [Model Information]
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Based on phi-3.5-mini-Instruct, this model is a general-purpose model with improved performance from the base model after employing multiple tuning methods. In particular, Japanese language performance has been improved.
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phi-3.5-mini-Instructをベースとして、複数のチューニング手法を採用のうえ、汎用的にベースモデルから性能を向上させたモデルです。特に日本語性能が向上しています。
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### [Benchmark Results]
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TODO:
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### 推奨される使用ガイドライン / Recommended Usage Guidelines
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1. **商用利用**: 本モデルを商用目的で使用する場合、info@axcxept.com へのメール連絡を強く推奨します。これにより、モデルの応用や改善についての協力の機会が生まれる可能性があります。
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2. **クレジット表記**: 本モデルを使用または改変する際は、以下のようなクレジット表記を行うことを推奨します:
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"This project utilizes HODACHI/Borea-Phi-3.5-mini-Instruct-Jp, a model based on Phi-3.5-mini-Instruct and fine-tuned by Axcxept co., ltd."
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3. **フィードバック**: モデルの使用経験に関するフィードバックを歓迎します。info@axcxept.com までご連絡ください。
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これらは推奨事項であり、法的要件ではありません。
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1. **Commercial Use**: If you plan to use this model for commercial purposes, we strongly encourage you to inform us via email at info@axcxept.com. This allows for potential collaboration on model applications and improvements.
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2. **Attribution**: When using or adapting this model, we recommend providing attribution as follows:
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"This project utilizes HODACHI/Borea-Phi-3.5-mini-Instruct-Jp, a model based on Phi-3.5-mini-Instruct and fine-tuned by Axcxept co., ltd."
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3. **Feedback**: We welcome any feedback on your experience with the model. Please feel free to email us at info@axcxept.com.
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Please note that these are recommendations and not legal requirements.
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### [Usage]
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Here are some code snippets to quickly get started with the model. First, run:
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```bash
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pip install flash_attn==2.5.8
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pip install accelerate==0.31.0
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pip install transformers==4.43.0
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pip install -U trl
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pip install pytest
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```
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Then, copy the snippet from the relevant section for your use case.
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以下に、モデルの実行を素早く開始するためのコードスニペットをいくつか紹介します。
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まず、
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```bash
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pip install flash_attn==2.5.8
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pip install accelerate==0.31.0
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pip install transformers==4.43.0
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pip install -U trl
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pip install pytest
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```
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を実行し、使用例に関連するセクションのスニペットをコピーしてください。
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