Update README.md

README.md

@@ -1,199 +1,154 @@
 ---
+license: mit
 library_name: transformers
-tags: []
+pipeline_tag: text-generation
+tags:
+- conversational
+language:
+- ja
+- en
 ---
 
-# Model Card for Model ID
 
-<!-- Provide a quick summary of what the model is/does. -->
+# [BOREA model card]
 
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/657e900beaad53ff67ba84db/uPWIuw_wAOwRk9O8qlZxZ.png)
 
 
-## Model Details
+## [Model Information]
+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.
 
-### Model Description
+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。
 
-<!-- Provide a longer summary of what this model is. -->
 
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
+### [Benchmark Results]
+TODO:
 
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
+### 推奨される使用ガイドライン / Recommended Usage Guidelines
 
-### Model Sources [optional]
+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。
 
-<!-- Provide the basic links for the model. -->
+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：
+   "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."
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+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。
 
-## Uses
+これらは推奨事項であり、法的要件ではありません。
 
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+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.
 
-### Direct Use
+2. **Attribution**: When using or adapting this model, we recommend providing attribution as follows:
+   "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."
 
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+3. **Feedback**: We welcome any feedback on your experience with the model. Please feel free to email us at info@axcxept.com.
 
-[More Information Needed]
+Please note that these are recommendations and not legal requirements. 
 
-### Downstream Use [optional]
 
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+### [Usage]
 
-[More Information Needed]
+Here are some code snippets to quickly get started with the model. First, run:
+```bash
+pip install flash_attn==2.5.8
+pip install accelerate==0.31.0
+pip install transformers==4.43.0
+pip install -U trl
+pip install pytest
+```
+Then, copy the snippet from the relevant section for your use case.
 
-### Out-of-Scope Use
+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。
+まず、
+```bash
+pip install flash_attn==2.5.8
+pip install accelerate==0.31.0
+pip install transformers==4.43.0
+pip install -U trl
+pip install pytest
+```
+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。
 
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+### [Chat Template]
+```
+<|system|>
+あなたは日本語能力が高い高度なAIです。特別な指示がない限り日本語で返答してください。<|end|>
+<|user|>
+「生き物デザイナー」という職業があります。これは、自分が考えたオリジナルの生き物をデザインし、実際にDNAを編集して作り出す仕事です。あなたが生き物デザイナーである場合、どんな生き物を作りたいですか？また、その生き物が持つ特徴や能力について説明してください。
+<|end|>
+<|assistant|>
+```
 
-[More Information Needed]
 
-## Bias, Risks, and Limitations
+### Loading the model locally
+After obtaining the Phi-3.5-mini-instruct model checkpoint, users can use this sample code for inference.
 
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
 
-[More Information Needed]
+torch.random.manual_seed(0)
 
-### Recommendations
+model = AutoModelForCausalLM.from_pretrained(
+    "microsoft/HODACHI/Borea-Phi-3.5-mini-Instruct-Jp", 
+    device_map="cuda", 
+    torch_dtype="auto", 
+    trust_remote_code=True, 
+)
+tokenizer = AutoTokenizer.from_pretrained("microsoft/Phi-3.5-mini-instruct")
 
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+messages = [
+    {"role": "system", "content": "あなたは日本語能力が高い高度なAIです。特別な指示がない限り日本語で返答してください。"},
+    {"role": "user", "content": "「生き物デザイナー」という職業があります。これは、自分が考えたオリジナルの生き物をデザインし、実際にDNAを編集して作り出す仕事です。あなたが生き物デザイナーである場合、どんな生き物を作りたいですか？また、その生き物が持つ特徴や能力について説明してください。"},
+]
 
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+pipe = pipeline(
+    "text-generation",
+    model=model,
+    tokenizer=tokenizer,
+)
 
-## How to Get Started with the Model
+generation_args = {
+    "max_new_tokens": 1024,
+    "return_full_text": False,
+    "temperature": 0.0,
+    "do_sample": False,
+}
 
-Use the code below to get started with the model.
+output = pipe(messages, **generation_args)
+print(output[0]['generated_text'])
+```
 
-[More Information Needed]
+Notes: If you want to use flash attention, call _AutoModelForCausalLM.from_pretrained()_ with _attn_implementation="flash_attention_2"_
 
-## Training Details
 
-### Training Data
+### [Model Data]
+#### Training Dataset]
+We extracted high-quality data from Japanese Wikipedia and FineWeb to create instruction data. Our innovative training approach allows for performance improvements across various languages and domains, making the model suitable for global use despite its focus on Japanese data.
 
-<!-- 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. -->
+日本語のWikiデータおよび、FineWebから良質なデータのみを抽出し、Instructionデータを作成しました。このモデルでは日本語に特化させていますが、世界中のどんなユースケースでも利用可能なアプローチです。
 
-[More Information Needed]
+https://huggingface.co/datasets/legacy-datasets/wikipedia
+https://huggingface.co/datasets/HuggingFaceFW/fineweb
 
-### Training Procedure
+#### Data Preprocessing
+We used a plain instruction tuning method to train the model on exemplary responses. This approach enhances the model's ability to understand and generate high-quality responses across various languages and contexts.
 
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+プレインストラクトチューニング手法を用いて、模範的回答を学習させました。この手法により、モデルは様々な言語やコンテキストにおいて高品質な応答を理解し生成する能力が向上しています。
 
-#### Preprocessing [optional]
+#### Implementation Information
+[Pre-Instruction Training] 
 
-[More Information Needed]
+https://huggingface.co/instruction-pretrain/instruction-synthesizer
 
-
-#### Training Hyperparameters
-
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-
-#### Speeds, Sizes, Times [optional]
-
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
-
-[More Information Needed]
-
-## Evaluation
-
-<!-- This section describes the evaluation protocols and provides the results. -->
-
-### Testing Data, Factors & Metrics
-
-#### Testing Data
-
-<!-- This should link to a Dataset Card if possible. -->
-
-[More Information Needed]
-
-#### Factors
-
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
-
-[More Information Needed]
-
-#### Metrics
-
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-
-[More Information Needed]
-
-### Results
-
-[More Information Needed]
-
-#### Summary
-
-
-
-## Model Examination [optional]
-
-<!-- Relevant interpretability work for the model goes here -->
-
-[More Information Needed]
-
-## Environmental Impact
-
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-
-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).
-
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-
-## Technical Specifications [optional]
-
-### Model Architecture and Objective
-
-[More Information Needed]
-
-### Compute Infrastructure
-
-[More Information Needed]
-
-#### Hardware
-
-[More Information Needed]
-
-#### Software
-
-[More Information Needed]
-
-## Citation [optional]
-
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
-
-**BibTeX:**
-
-[More Information Needed]
-
-**APA:**
-
-[More Information Needed]
-
-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-
-[More Information Needed]
-
-## More Information [optional]
-
-[More Information Needed]
-
-## Model Card Authors [optional]
-
-[More Information Needed]
-
-## Model Card Contact
-
-[More Information Needed]
+### [Disclaimer]
+このモデルは研究開発のみを目的として提供されるものであり、実験的なプロトタイプとみなされるべきモデルです。
+商業的な使用やミッションクリティカルな環境への配備を意図したものではありません。
+本モデルの使用は、使用者の責任において行われるものとし、その性能および結果は保証されません。
+Axcxept株式会社は、直接的、間接的、特別、偶発的、結果的な損害、または本モデルの使用から生じるいかなる損失に対しても、得られた結果にかかわらず、一切の責任を負いません。
+利用者は、本モデルの使用に伴うリスクを十分に理解し、自己の判断で使用するものとします。
+
+### [Hardware]
+H100PCIe × 8(Running in 2h)
+
+### [We are.]
+[![Axcxept logo](https://cdn-uploads.huggingface.co/production/uploads/657e900beaad53ff67ba84db/8OKW86U986ywttvL2RcbG.png)](https://axcxept.com)