Update README.md

README.md

@@ -6,17 +6,48 @@ tags:
 - unsloth
 - llama
 - trl
-license: apache-2.0
+license: cc
 language:
-- en
+- ja
+datasets:
+- elyza/ELYZA-tasks-100
+- weblab-GENIAC/aya-ja-evol-instruct-calm3-dpo-masked
 ---
 
 # Uploaded  model
 
 - **Developed by:** JunichiroMorita
-- **License:** apache-2.0
+- **License:** CC-BY-NC-SA
 - **Finetuned from model :** llm-jp/llm-jp-3-13b
 
-This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
+# Usage
+```python
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM
+tokenizer = AutoTokenizer.from_pretrained("JunichiroMorita/llm-jp-3-13b_lora_20241201")
+model = AutoModelForCausalLM.from_pretrained("JunichiroMorita/llm-jp-3-13b_lora_20241201", device_map="auto", torch_dtype=torch.bfloat16)
+chat = [
+    {"role": "system", "content": "以下は、タスクを説明する指示です。要求を適切に満たす応答を書きなさい。"},
+    {"role": "user", "content": "自然言語処理とは何か"},
+]
+tokenized_input = tokenizer.apply_chat_template(chat, add_generation_prompt=True, tokenize=True, return_tensors="pt").to(model.device)
+with torch.no_grad():
+    output = model.generate(
+        tokenized_input,
+        max_new_tokens=2048,
+        do_sample=True,
+        top_p=0.95,
+        temperature=0.7,
+        repetition_penalty=1.05,
+    )[0]
+print(tokenizer.decode(output))
 
-[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
+```
+
+# Data
+- [DeL-TaiseiOzaki/news_summary_2024secondhalf](https://huggingface.co/datasets/DeL-TaiseiOzaki/news_summary_2024secondhalf)
+- [llmのための日本語インストラクションデータ (CC-BY-NC-SA)](https://liat-aip.sakura.ne.jp/wp/llm%e3%81%ae%e3%81%9f%e3%82%81%e3%81%ae%e6%97%a5%e6%9c%ac%e8%aa%9e%e3%82%a4%e3%83%b3%e3%82%b9%e3%83%88%e3%83%a9%e3%82%af%e3%82%b7%e3%83%a7%e3%83%b3%e3%83%87%e3%83%bc%e3%82%bf%e4%bd%9c%e6%88%90/llm%e3%81%ae%e3%81%9f%e3%82%81%e3%81%ae%e6%97%a5%e6%9c%ac%e8%aa%9e%e3%82%a4%e3%83%b3%e3%82%b9%e3%83%88%e3%83%a9%e3%82%af%e3%82%b7%e3%83%a7%e3%83%b3%e3%83%87%e3%83%bc%e3%82%bf-%e5%85%ac%e9%96%8b/)\[1]
+- [elyza/ELYZA-tasks-100](https://huggingface.co/datasets/elyza/ELYZA-tasks-100)
+- [weblab-GENIAC/aya-ja-evol-instruct-calm3-dpo-masked](https://huggingface.co/datasets/weblab-GENIAC/aya-ja-evol-instruct-calm3-dpo-masked)
+
+\[1]: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)