需要基于BERT文本分类和Django可视化系统的代码

以下是基于BERT文本分类和Django可视化系统的代码：

## 1. 安装依赖包

pip install transformers
pip install torch
pip install django

## 2. 训练BERT模型

from transformers import BertTokenizer, BertForSequenceClassification
import torch

# 加载预训练模型和tokenizer
tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')
model = BertForSequenceClassification.from_pretrained('bert-base-uncased', num_labels=2)

# 准备数据
sentences = ["I love you.", "I hate you."]
labels = [1, 0]

inputs = tokenizer(sentences, padding=True, truncation=True, return_tensors="pt")
labels = torch.tensor(labels).unsqueeze(0)

# 训练模型
outputs = model(**inputs, labels=labels)
loss = outputs.loss
logits = outputs.logits

# 保存模型
torch.save(model.state_dict(), "bert_model.pth")

## 3. 创建Django项目

django-admin startproject bert_classification
cd bert_classification

## 4. 创建Django app

python manage.py startapp classifier

## 5. 编写分类器

from django.apps import AppConfig
from transformers import BertTokenizer, BertForSequenceClassification
import torch

class ClassifierConfig(AppConfig):
    name = 'classifier'
    model_path = "bert_model.pth"
    tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')
    model = BertForSequenceClassification.from_pretrained('bert-base-uncased', num_labels=2)
    model.load_state_dict(torch.load(model_path, map_location=torch.device('cpu')))
    model.eval()

    def classify(self, sentence):
        inputs = self.tokenizer(sentence, padding=True, truncation=True, return_tensors="pt")
        outputs = self.model(**inputs)
        logits = outputs.logits
        probabilities = torch.softmax(logits, dim=1).detach().tolist()[0]
        return probabilities

## 6. 编写视图函数

from django.shortcuts import render
from classifier.apps import ClassifierConfig

def index(request):
    if request.method == "POST":
        sentence = request.POST["sentence"]
        probabilities = ClassifierConfig.classify(ClassifierConfig(), sentence)
        return render(request, "classifier/result.html", {"probabilities": probabilities})
    else:
        return render(request, "classifier/index.html")

## 7. 编写模板

<!-- classifier/templates/classifier/index.html -->

<form method="POST">
    {% csrf_token %}
    <label for="sentence">Sentence:</label>
    <input type="text" name="sentence" id="sentence">
    <button type="submit">Classify</button>
</form>

<!-- classifier/templates/classifier/result.html -->

{% if probabilities.0 > probabilities.1 %}
    <p>Positive</p>
{% else %}
    <p>Negative</p>
{% endif %}

## 8. 配置URL

from django.urls import path
from classifier.views import index

urlpatterns = [
    path('', index, name='index'),
]

## 9. 运行Django项目

python manage.py runserver

现在可以在浏览器中访问 `http://localhost:8000/`，输入一句话进行分类。