| """Offline contracted scientific decision. MycelAI, Apache-2.0.""" |
| import argparse |
| import json |
| from pathlib import Path |
|
|
| import torch |
| from transformers import AutoModel, AutoTokenizer |
|
|
| parser = argparse.ArgumentParser() |
| parser.add_argument("--model", type=Path, default=Path(__file__).resolve().parent) |
| parser.add_argument("--device", default="cuda") |
| args = parser.parse_args() |
| tokenizer = AutoTokenizer.from_pretrained(args.model, trust_remote_code=True, local_files_only=True) |
| model = AutoModel.from_pretrained(args.model, trust_remote_code=True, |
| local_files_only=True, dtype=torch.bfloat16) |
| model.prepare_for_inference(args.device) |
| result = model.predict(tokenizer, task="study_approach", text=( |
| "Title: A synthetic benchmark for sorting algorithms\n" |
| "Abstract: We compare algorithmic time complexity using generated arrays " |
| "and prove a bound for a new sorting method.")) |
| print(json.dumps(result, indent=2)) |
|
|
