Update README.md and Add LICENSE

LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2025 SB Intuitions
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

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 ---
-base_model: []
-library_name: transformers
-tags:
-- mit
-
+license: mit
+language:
+- ja
+pipeline_tag: text-generation
+base_model:
+  - sbintuitions/sarashina2.2-0.5b
 ---
 
-# <model_name>
+# sbintuitions/sarashina2.2-0.5b-instruct-v0.1
+
+## Model Summary
+
+This repository provides Japanese language models trained by [SB Intuitions](https://www.sbintuitions.co.jp/).
+
+## Model Details
+
+- Model type: Autoregressive Language Model
+- Language(s): Japanese
+
+## How to use
+
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline, set_seed
+
+# モデルのロード
+model_name = "sbintuitions/sarashina2.2-0.5b-instruct-v0.1"
+model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+chat_pipeline = pipeline("text-generation", model=model, tokenizer=tokenizer)
+set_seed(123)
+
+# ユーザーの入力
+user_input = [{"role": "user", "content": "こんにちは。あなたの名前を教えて"}]
+
+# モデルによる応答生成
+responses = chat_pipeline(
+    user_input,
+    max_length=50,
+    do_sample=True,
+    num_return_sequences=3,
+)
+
+# 応答を表示
+for i, response in enumerate(responses, 1):
+    print(f"Response {i}: {response['generated_text']}")
+
+# Response 1: [{'role': 'user', 'content': 'こんにちは。あなたの名前を教えて'}, {'role': 'assistant', 'content': 'Sarashina2と言います。本日のご要件を教えて下さい。'}]
+# Response 2: [{'role': 'user', 'content': 'こんにちは。あなたの名前を教えて'}, {'role': 'assistant', 'content': 'こんにちは！私の名前はSarashina2です。今日はどうしましたか？'}]
+# Response 3: [{'role': 'user', 'content': 'こんにちは。あなたの名前を教えて'}, {'role': 'assistant', 'content': 'Sarashina2と言います。本日のご要件を教えて下さい。'}]
+```
+
+## Limitations
+
+This model has limited safety training.
+Therefore, it might generate some meaningless sequences, some inaccurate instances, or biased/objectionable outputs.
+Before using it, we would like developers to tune models based on human preferences and safety considerations.
+
+## License
+
+MIT License