deepseek本地部署个性化deepsea个人整合包

deepseek 本地部署 个性化 deepsea个人整合包

DeepSeek是一个基于深度学习的个性化推荐系统，可以用于本地部署。以下是一个简单的DeepSeek本地部署示例：

pip install numpy pandas scikit-learn matplotlib seaborn

import osimport sysimport jsonimport numpy as npimport pandas as pdfrom sklearn.model_selection import train_test_splitfrom sklearn.metrics import accuracy_scorefrom sklearn.ensemble import RandomForestClassifierfrom sklearn.feature_extraction.text import CountVectorizerfrom sklearn.pipeline import Pipelinefrom sklearn.preprocessing import StandardScalerfrom sklearn.svm import SVCfrom sklearn.utils import class_weightfrom deepseek import DeepSeek# 加载数据data = pd.read_csv("data.csv")# 文本预处理vectorizer = CountVectorizer()X = vectorizer.fit_transform(data["text"])y = data["label"]# 划分训练集和测试集X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)# 创建管道pipeline = Pipeline([    ("vect", vectorizer),    ("clf", RandomForestClassifier(class_weight="balanced")),])# 训练模型pipeline.fit(X_train, y_train)# 预测predictions = pipeline.predict(X_test)# 评估模型accuracy = accuracy_score(y_test, predictions)print("Accuracy: ", accuracy)# 保存模型with open("deepseek_local_deployment.pkl", "wb") as f:    pickle.dump(pipeline, f)

name, textAlice, I love coding!Bob, Python is awesome.Charlie, I enjoy playing sports.

python deepseek_local_deployment.py