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import transformers | |
class LLMInferenceServer: | |
def __init__(self, model_name): | |
self.model = transformers.AutoModelForCausalLM.from_pretrained(model_name) | |
def generate(self, prompt, max_length=100): | |
inputs = transformers.InputFeatures(input_ids=[self.model.config.bos_token_id], attention_mask=[1]) | |
output = self.model.generate(inputs, max_length=max_length, prompt=prompt) | |
return output[0] | |
if __name__ == '__main__': | |
model_name = "google/bigbird-roberta-base" | |
server = LLMInferenceServer(model_name) | |
from flask import Flask, request, jsonify | |
app = Flask(__name__) | |
def generate(): | |
prompt = request.json["prompt"] | |
max_length = request.json["max_length"] | |
response = server.generate(prompt, max_length) | |
return jsonify({"response": response}) | |
app.run(host="0.0.0.0", port=8000) | |