Update README

README.md

@@ -1,3 +1,87 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+datasets:
+- kinokokoro/ichikara-instruction-003
+language:
+- ja
+base_model:
+- llm-jp/llm-jp-3-13b
+library_name: transformers
+tags:
+- text-generation-inference
+- transformers
+---
+
+# Sample Use
+```python
+MODEL_DIR = os.path.join("model_dir")
+
+def load_model():
+    print("モデルとトークナイザーを読み込み中...")
+    tokenizer = AutoTokenizer.from_pretrained(MODEL_DIR)
+    model = AutoModelForCausalLM.from_pretrained(
+        MODEL_DIR,
+        torch_dtype=torch.float16,
+        device_map={"": 0},  # 明示的にGPU割り当て
+        use_cache=True,      # キャッシュを有効化
+    ).to('cuda')            # 明示的にGPUへ
+
+    model.eval()  # 評価モード
+    return model, tokenizer
+
+def generate_predictions(model, tokenizer, input_file, output_file):
+    # バッチ処理の追加
+    BATCH_SIZE = 8  # バッチサイズの設定
+
+    print(f"入力ファイルを読み込み中: {input_file}")
+    tasks = []
+    with open(input_file, 'r', encoding='utf-8') as f:
+        for line in f:
+            tasks.append(json.loads(line))
+
+    results = []
+    print("推論を実行中...")
+
+    # バッチ処理
+    for i in tqdm(range(0, len(tasks), BATCH_SIZE)):
+        batch_tasks = tasks[i:i + BATCH_SIZE]
+        prompts = [f"入力: {task['input']}\n出力: " for task in batch_tasks]
+
+        # バッチでの推論
+        inputs = tokenizer(
+            prompts,
+            return_tensors="pt",
+            padding=True,
+            truncation=True,
+            max_length=512
+        ).to('cuda')
+
+        with torch.no_grad():
+            outputs = model.generate(
+                inputs.input_ids,
+                max_length=512,
+                temperature=0.7,
+                do_sample=False,
+                repetition_penalty=1.2,
+                pad_token_id=tokenizer.pad_token_id,
+                num_return_sequences=1,
+                early_stopping=True,    # 早期停止を有効化
+                use_cache=True          # キャッシュを使用
+            )
+
+        # バッチ出力の処理
+        for j, output in enumerate(outputs):
+            generated_text = tokenizer.decode(output, skip_special_tokens=True)
+            output_text = generated_text.split("出力: ")[-1].strip()
+
+            results.append({
+                "task_id": batch_tasks[j]["task_id"],
+                "output": output_text
+            })
+
+    print(f"結果を保存中: {output_file}")
+    with open(output_file, 'w', encoding='utf-8') as f:
+        for result in results:
+            json.dump(result, f, ensure_ascii=False)
+            f.write('\n')
+```