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from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
MODEL_REPO = "Rahul-8799/software_engineer_mellum"
tokenizer = AutoTokenizer.from_pretrained(MODEL_REPO)
model = AutoModelForCausalLM.from_pretrained(MODEL_REPO, device_map="auto", torch_dtype=torch.float16)
model.eval()
def run(prompt):
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
with torch.no_grad():
outputs = model.generate(**inputs, max_new_tokens=512)
return tokenizer.decode(outputs[0], skip_special_tokens=True) |