ArekuNoimar
/

llama-2-7b-hf-instruct-chatbot-arena-ja-v3

@@ -1,199 +1,79 @@
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 library_name: transformers
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 ---
+license: llama2
+language:
+- ja
+- en
 library_name: transformers
+tags:
+- japanese
+datasets:
+- cyberagent/chatbot-arena-ja-calm2-7b-chat-experimental
+base_model:
+- meta-llama/Llama-2-7b-hf
 ---
+## llama-2-7b-hf-instruct-chatbot-arena-ja-v3
+## モデルについて
+このモデルはmeta/llama-2-7b-hfにcyberagent/chatbot-arena-ja-calm2-7b-chat-experimentalデータセットを使用し、QLoRAでFine-Tuningを実施したモデルです。
+## 注意点
+QLoRAでトレーニングを実施しておりますが、アップロードされている重みはベースモデルのmeta/llama-2-7b-hfとトレーニングした重みのアダプターをPeftライブラリでマージしたものになっています。
+その為、量子化設定を利用しない場合は意図した精度と異なる動作をする場合があります。
+## 使い方
+```python
+from huggingface_hub import snapshot_download
+from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer, BitsAndBytesConfig
+import torch
+def generate_response(model, tokenizer, prompt, device):
+    """
+    指定されたプロンプトに対して、モデルを用いてテキスト生成を実行し、
+    生成されたテキスト応答を返却する関数です。
+    Args:
+        model: 使用する因果言語モデル (AutoModelForCausalLM)
+        tokenizer: モデルに対応するトークナイザー (AutoTokenizer)
+        prompt: テキスト生成の入力として与えるプロンプト文字列
+        device: テンソルを転送するデバイス（例: "cuda" や "cpu"）
+    Returns:
+        生成されたテキスト応答（特殊トークンを除外してデコード済みの文字列）
+    """
+    inputs = tokenizer(prompt, return_tensors="pt") # テンソル変換
+    inputs = {key: tensor.to(device) for key, tensor in inputs.items()} # デバイスに転送
+    output = model.generate(**inputs, streamer=streamer) # TextStreamerを用いてテキスト生成を実行
+    return tokenizer.decode(output[0], skip_special_tokens=True, max_new_tokens=1024) # 生成されたトークンをデコード
+device = "cuda" # 使用するデバイスを "cuda" （GPU）に設定
+prompt = "AIについて簡潔に教えてください。" # テキスト生成用の入力プロンプトを定義
+# 量子化の設定: 8-bitロードを行い、4-bit計算時にtorch.float16を使用する設定を適用
+bnb_config = BitsAndBytesConfig(
+    load_in_4bit=True,                # モデルを4bitでロードする設定
+    bnb_4bit_use_double_quant=True,   # 二重量子化の使用を指定
+    bnb_4bit_quant_type="nf4",        # 量子化タイプを「nf4」に設定
+    bnb_4bit_compute_dtype=torch.bfloat16,  # 計算時のデータ型をbfloat16に設定
+)
+# モデルをダウンロード
+model_name = snapshot_download(
+    repo_id="ArekuNoimar/llama-2-7b-hf-instruct-chatbot-arena-ja-v3" # モデルのリポジトリID
+)
+# 量子化設定およびデバイスマッピングを適用
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,                      # ダウンロードしたモデルのパス
+    device_map=device,               # テンソルを動作させるデバイス（"cuda"）を指定
+    quantization_config=bnb_config,  # 設定した量子化設定を適用
+    torch_dtype=torch.bfloat16       # モデルの計算に使用するデータ型をbfloat16に指定
+)
+tokenizer = AutoTokenizer.from_pretrained(model_name) # トークナイザーの読み込み
+streamer = TextStreamer(tokenizer, skip_prompt=False, skip_special_tokens=False) # TextStreamerを初期化
+generate_response(model, tokenizer, prompt, device) # 関数を呼び出してテキストを生成
+```