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af43127 45a78fe af43127 45a78fe af43127 45a78fe | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 | # handler.py
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM
MODEL_PATH = "."
class EndpointHandler:
def __init__(self, path=""):
print("Loading merged model...")
self.tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH, trust_remote_code=True)
self.model = AutoModelForCausalLM.from_pretrained(
MODEL_PATH, torch_dtype=torch.float16, device_map="auto", trust_remote_code=True
)
self.model.eval()
print("Model loaded successfully.")
def __call__(self, data):
prompt = data.get("inputs", "")
inputs = self.tokenizer(prompt, return_tensors="pt").to(self.model.device)
with torch.no_grad():
outputs = self.model.generate(
**inputs,
max_new_tokens=512,
temperature=0.7,
top_p=0.9,
do_sample=True,
pad_token_id=self.tokenizer.eos_token_id,
eos_token_id=self.tokenizer.eos_token_id,
)
return {"generated_text": self.tokenizer.decode(outputs[0], skip_special_tokens=True)}
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