Update README.md

README.md

@@ -1,199 +1,135 @@
 ---
 library_name: transformers
-tags: []
+tags:
+- llm-jp
+- japanese
+- instruction-tuning
 ---
 
-# Model Card for Model ID
-
-<!-- Provide a quick summary of what the model is/does. -->
-
-
+# Model Card for yuhkis/llm-jp-3-13b-finetune
 
 ## Model Details
 
 ### Model Description
 
-<!-- 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.
-
-- **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]
+This is a LoRA-tuned version of LLM-jp-3-13b, fine-tuned on the Ichikara Instruction dataset.
 
-### Model Sources [optional]
-
-<!-- Provide the basic links for the model. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+- **Developed by:** Yuhki Shiraishi
+- **Model type:** Instruction-tuned Japanese Language Model
+- **Language:** Japanese
+- **License:** CC-BY-NC-SA
+- **Finetuned from model:** llm-jp/llm-jp-3-13b
 
 ## Uses
 
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-
 ### Direct Use
 
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+To use this model for inference:
 
-[More Information Needed]
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
+import torch
 
-### Downstream Use [optional]
+model_id = "yuhkis/llm-jp-3-13b-finetune"
+bnb_config = BitsAndBytesConfig(
+    load_in_4bit=True,
+    bnb_4bit_quant_type="nf4",
+    bnb_4bit_compute_dtype=torch.bfloat16,
+)
 
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    quantization_config=bnb_config,
+    device_map="auto",
+    token=HF_TOKEN
+)
+tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True, token=HF_TOKEN)
+```
 
-[More Information Needed]
+### Output Format
 
-### Out-of-Scope Use
+The model outputs results in JSONL format with required fields:
+- task_id: Task identifier
+- output: Generated response
 
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+Example output:
+```json
+{"task_id": 0, "output": "応答テキスト"}
+```
 
-[More Information Needed]
+### Out-of-Scope Use
 
-## Bias, Risks, and Limitations
+This model should not be used for:
+- Commercial applications due to license restrictions
+- Critical decision-making without human oversight
+- Applications requiring strict reliability guarantees
 
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+## Bias, Risks, and Limitations
 
-[More Information Needed]
+- The model inherits biases from its training data
+- Output quality may vary depending on input complexity
+- The model should not be used for making critical decisions without human oversight
 
 ### Recommendations
 
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
-
-## How to Get Started with the Model
-
-Use the code below to get started with the model.
-
-[More Information Needed]
+Users should be aware of the model's limitations and verify outputs when used in applications.
 
 ## Training Details
 
 ### Training 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. -->
-
-[More Information Needed]
-
-### Training Procedure
-
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-
-#### Preprocessing [optional]
-
-[More Information Needed]
-
-
-#### 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]
+- Dataset: Ichikara Instruction Dataset
 
-#### Factors
+### Training Procedure 
 
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+- **Training regime:** bf16 mixed precision
+- **Library:** 🤗 Transformers
+- **Optimization:** LoRA (Low-Rank Adaptation)
 
-[More Information Needed]
+## Technical Specifications
 
-#### Metrics
+### Model Architecture
 
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+- Base model: LLM-jp-3-13b
+- Adaptation method: LoRA
 
-[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. -->
+## Citation
 
 **BibTeX:**
+```bibtex
+@misc{shiraishi2024llm,
+    title={LLM-jp-3-13b-finetune: Instruction-tuned Japanese Language Model},
+    author={Yuhki Shiraishi},
+    year={2024},
+    publisher={Hugging Face},
+    howpublished={\url{https://huggingface.co/yuhkis/llm-jp-3-13b-finetune}}
+}
+```
+
+**Base Model Citation:**
+```bibtex
+@misc{llm-jp2024,
+    title={LLM-jp-3: Large Language Model for Japanese},
+    author={LLM-jp Project Team},
+    year={2024},
+    publisher={Hugging Face},
+    howpublished={\url{https://huggingface.co/llm-jp/llm-jp-3-13b}}
+}
+```
+
+**Training Data Citation:**
+```
+関根聡, 安藤まや, 後藤美知子, 鈴木久美, 河原大輔, 井之上直也, 乾健太郎. 
+ichikara-instruction: LLMのための日本語インストラクションデータの構築. 
+言語処理学会第30回年次大会(2024)
+```
 
-[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]
+## Model Card Contact
 
-[More Information Needed]
+**Primary Contact:**
+- Name: Yuhki Shiraishi
+- GitHub: [@yuhkis](https://github.com/yuhkis)
 
-## Model Card Contact
+For questions regarding this model, please open an issue in the GitHub repository or contact via HuggingFace discussion forum.
 
-[More Information Needed]
+Please include "LLM-jp-3-13b-finetune" in the subject line of any correspondence.