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import os
os.system("pip install torch sentencepiece transformers Xformers accelerate")
import gradio as gr
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
# モデルとトークナイザの初期化
model = AutoModelForCausalLM.from_pretrained("cyberagent/open-calm-1b", device_map="auto", torch_dtype=torch.float16)
tokenizer = AutoTokenizer.from_pretrained("cyberagent/open-calm-1b")
# 推論用の関数
def generate_text(input_text):
inputs = tokenizer(input_text, return_tensors="pt").to(model.device)
with torch.no_grad():
tokens = model.generate(
**inputs,
max_new_tokens=64,
do_sample=True,
temperature=0.7,
top_p=0.9,
repetition_penalty=1.05,
pad_token_id=tokenizer.pad_token_id,
)
output = tokenizer.decode(tokens[0], skip_special_tokens=True)
return output
# 入力と出力のインターフェースを作成
input_text = gr.inputs.Textbox(lines=2, label="入力テキスト")
output_text = gr.outputs.Textbox(label="生成されたテキスト")
# インターフェースを作成
iface = gr.Interface(fn=generate_text, inputs=input_text, outputs=output_text)
# GUIを起動
iface.launch()
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