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Update app.py
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app.py
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@@ -5,7 +5,8 @@ import spaces
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from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer
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import os
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from threading import Thread
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-
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HF_TOKEN = os.environ.get("HF_TOKEN", None)
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MODEL_ID = "TeamDelta/mistral-yuki-7B"
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@@ -42,14 +43,19 @@ h3 {
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}
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"""
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model = AutoModelForCausalLM.from_pretrained(
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tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
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@spaces.GPU
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def stream_chat(message: str, history: list, temperature: float, max_new_tokens: int, top_p: float, top_k: int, penalty: float):
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print(f'message is - {message}')
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@@ -59,8 +65,6 @@ def stream_chat(message: str, history: list, temperature: float, max_new_tokens:
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conversation.extend([{"role": "user", "content": prompt}, {"role": "assistant", "content": answer}])
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conversation.append({"role": "user", "content": message})
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#print(f"Conversation is -\n{conversation}")
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input_ids = tokenizer.apply_chat_template(conversation, tokenize=False, add_generation_prompt=True)
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inputs = tokenizer(input_ids, return_tensors="pt").to(0)
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@@ -75,7 +79,7 @@ def stream_chat(message: str, history: list, temperature: float, max_new_tokens:
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max_new_tokens=max_new_tokens,
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do_sample=True,
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temperature=temperature,
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eos_token_id
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)
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thread = Thread(target=model.generate, kwargs=generate_kwargs)
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@@ -86,8 +90,6 @@ def stream_chat(message: str, history: list, temperature: float, max_new_tokens:
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buffer += new_text
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yield buffer
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chatbot = gr.Chatbot(height=500)
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with gr.Blocks(css=CSS) as demo:
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@@ -144,16 +146,9 @@ with gr.Blocks(css=CSS) as demo:
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render=False,
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),
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],
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examples=
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["超能力を持つ主人公のSF物語のシナリオを考えてください。伏線の設定、テーマやログラインを理論的に使用してください"],
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["子供の夏休みの自由研究のための、5つのアイデアと、その手法を簡潔に教えてください。"],
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["パズルゲームのスクリプト作成のためにアドバイスお願いします"],
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["マークダウン記法にて、ブロック崩しのゲーム作成の教科書作成してください"],
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],
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cache_examples=False,
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)
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if __name__ == "__main__":
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demo.launch()
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from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer
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import os
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from threading import Thread
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import random
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from datasets import load_dataset
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HF_TOKEN = os.environ.get("HF_TOKEN", None)
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MODEL_ID = "TeamDelta/mistral-yuki-7B"
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}
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"""
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# モデルとトークナイザーの読み込み
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model = AutoModelForCausalLM.from_pretrained(
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MODEL_ID,
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torch_dtype=torch.float16,
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device_map="auto",
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)
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tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
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# データセットをロードして10個の例を取得
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dataset = load_dataset("elyza/ELYZA-tasks-100")
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examples = random.sample(dataset['train'], 10)
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example_inputs = [example['input'] for example in examples]
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@spaces.GPU
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def stream_chat(message: str, history: list, temperature: float, max_new_tokens: int, top_p: float, top_k: int, penalty: float):
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print(f'message is - {message}')
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conversation.extend([{"role": "user", "content": prompt}, {"role": "assistant", "content": answer}])
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conversation.append({"role": "user", "content": message})
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input_ids = tokenizer.apply_chat_template(conversation, tokenize=False, add_generation_prompt=True)
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inputs = tokenizer(input_ids, return_tensors="pt").to(0)
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max_new_tokens=max_new_tokens,
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do_sample=True,
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temperature=temperature,
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eos_token_id=[128001, 128009],
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)
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thread = Thread(target=model.generate, kwargs=generate_kwargs)
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buffer += new_text
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yield buffer
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chatbot = gr.Chatbot(height=500)
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with gr.Blocks(css=CSS) as demo:
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render=False,
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),
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],
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examples=example_inputs,
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cache_examples=False,
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)
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if __name__ == "__main__":
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demo.launch()
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