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d214fc1 | 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 32 33 34 35 36 37 38 39 40 41 | from typing import Dict, Any
import torch
from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer
BASE_MODEL_ID = "unsloth/DeepSeek-R1-Distill-Llama-70B-unsloth-bnb-4bit"
class EndpointHandler:
def __init__(self, path=""):
self.tokenizer = AutoTokenizer.from_pretrained(BASE_MODEL_ID)
base_model = AutoModelForCausalLM.from_pretrained(
BASE_MODEL_ID,
torch_dtype=torch.bfloat16,
device_map="auto",
)
self.model = PeftModel.from_pretrained(base_model, path)
self.model.eval()
def __call__(self, data: Dict[str, Any]) -> Dict[str, Any]:
inputs = data.get("inputs", "")
parameters = data.get("parameters", {})
input_ids = self.tokenizer(
inputs, return_tensors="pt"
).input_ids.to(self.model.device)
with torch.no_grad():
output_ids = self.model.generate(
input_ids,
max_new_tokens=parameters.get("max_new_tokens", 256),
temperature=parameters.get("temperature", 0.7),
)
generated_text = self.tokenizer.decode(
output_ids[0], skip_special_tokens=True
)
return {"generated_text": generated_text} |