From 74541672bdb91b7108da8b74706ce70e6f34f1a8 Mon Sep 17 00:00:00 2001 From: Yang An Date: Tue, 12 Sep 2023 11:31:51 +0800 Subject: [PATCH] Update README_JA.md --- README_JA.md | 35 +++++++++++++---------------------- 1 file changed, 13 insertions(+), 22 deletions(-) diff --git a/README_JA.md b/README_JA.md index e5476c6..6490fd5 100644 --- a/README_JA.md +++ b/README_JA.md @@ -176,28 +176,19 @@ print(tokenizer.decode(pred.cpu()[0], skip_special_tokens=True)) ModelScope は、MaaS(Model-as-a-Service) のためのオープンソースプラットフォームであり、AI 開発者に柔軟で費用対効果の高いモデルサービスを提供します。同様に、以下のように ModelScope でモデルを実行することができます: ```python -import os -from modelscope.pipelines import pipeline -from modelscope.utils.constant import Tasks -from modelscope import snapshot_download - -model_id = 'QWen/qwen-7b-chat' -revision = 'v1.0.0' - -model_dir = snapshot_download(model_id, revision) - -pipe = pipeline( -task=Tasks.chat, model=model_dir, device_map='auto') -history = None - -text = '浙江省の省都はどこですか?' -results = pipe(text, history=history) -response, history = results['response'], results['history'] -print(f'Response: {response}') -text = '何がそんなに面白いのか?' -results = pipe(text, history=history) -response, history = results['response'], results['history'] -print(f'Response: {response}') +from modelscope import AutoModelForCausalLM, AutoTokenizer +from modelscope import GenerationConfig + +tokenizer = AutoTokenizer.from_pretrained("qwen/Qwen-7B-Chat", revision='v1.0.5', trust_remote_code=True) +model = AutoModelForCausalLM.from_pretrained("qwen/Qwen-7B-Chat", revision='v1.0.5', device_map="auto", trust_remote_code=True, fp16=True).eval() +model.generation_config = GenerationConfig.from_pretrained("Qwen/Qwen-7B-Chat", revision='v1.0.5', trust_remote_code=True) # 可指定不同的生成长度、top_p等相关超参 + +response, history = model.chat(tokenizer, "你好", history=None) +print(response) +response, history = model.chat(tokenizer, "浙江的省会在哪里?", history=history) +print(response) +response, history = model.chat(tokenizer, "它有什么好玩的景点", history=history) +print(response) ```