锦中人工智能助手

pip install transformers flask

from flask import Flask, request, jsonify

from transformers import pipeline

app = Flask(__name__)

# 加载预训练的大模型

model = pipeline("question-answering", model="deepset/roberta-base-squad2")

@app.route('/query', methods=['POST'])

def query():

data = request.get_json()

question = data['question']

context = data['context']

result = model(question=question, context=context)

return jsonify(result)

if __name__ == '__main__':

app.run(debug=True)

from transformers import AutoTokenizer, AutoModelForQuestionAnswering, Trainer, TrainingArguments

from datasets import load_dataset

tokenizer = AutoTokenizer.from_pretrained("deepset/roberta-base-squad2")

model = AutoModelForQuestionAnswering.from_pretrained("deepset/roberta-base-squad2")

dataset = load_dataset("squad")

tokenized_datasets = dataset.map(lambda examples: tokenizer(examples["question"], examples["context"], truncation=True), batched=True)

training_args = TrainingArguments(

output_dir="./results",

evaluation_strategy="epoch",

learning_rate=2e-5,

per_device_train_batch_size=16,

num_train_epochs=3,

weight_decay=0.01,

)

trainer = Trainer(

model=model,

args=training_args,

train_dataset=tokenized_datasets["train"],

eval_dataset=tokenized_datasets["validation"],

)

trainer.train()