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Class TrainConfig

examples/discrete_diffusion/train_llada2.py:38–65  ·  view source on GitHub ↗

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36
37@dataclass
38class TrainConfig:
39 model_name_or_path: str
40 dataset_name: str
41 dataset_config_name: Optional[str]
42 text_column: str
43 cache_dir: Optional[str]
44 use_dummy_data: bool
45 num_dummy_samples: int
46
47 output_dir: str
48 seed: int
49 max_train_steps: int
50 checkpointing_steps: int
51 logging_steps: int
52
53 per_device_train_batch_size: int
54 gradient_accumulation_steps: int
55 learning_rate: float
56 weight_decay: float
57 lr_scheduler: str
58 lr_warmup_steps: int
59
60 max_length: int
61 prompt_length: int
62 block_length: int
63
64 lambda_conf: float
65 conf_temperature: float
66
67
68def parse_args() -> TrainConfig:

Callers 1

parse_argsFunction · 0.85

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