File size: 1,968 Bytes
11c11f8 | 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 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 | from __future__ import annotations
import argparse
def train_main() -> None:
from train import _build_argparser, train
args = _build_argparser().parse_args()
train(args)
def train_fast_main() -> None:
from train_fast import train
parser = argparse.ArgumentParser(description="Chimera 5.2 Fast CPU training")
parser.add_argument("--config", default="config.json")
parser.add_argument("--scale", default="tiny", choices=["tiny", "small", "medium", "full"])
parser.add_argument("--seq_len", type=int, default=32)
parser.add_argument("--batch_size", type=int, default=4)
parser.add_argument("--lr", type=float, default=1e-3)
parser.add_argument("--warmup", type=int, default=100)
parser.add_argument("--max_steps", type=int, default=1000)
parser.add_argument("--max_samples", type=int, default=5000)
parser.add_argument("--bf16", action="store_true", default=False)
parser.add_argument("--compile", action="store_true", default=False)
parser.add_argument("--cache_dir", default="./cache")
parser.add_argument("--log_every", type=int, default=10)
parser.add_argument("--save_every", type=int, default=500)
parser.add_argument("--output_dir", default="./chimera_output")
train(parser.parse_args())
def train_hyper_main() -> None:
from train_hyper import benchmark, cli, train_hyper
args = cli().parse_args()
if args.max_samples and not args.max_tokens:
args.max_tokens = args.max_samples * (args.seq_len + 1)
if args.all:
args.growlength = True
args.reservoir = True
args.progressive_unfreeze = True
if args.benchmark:
args.growlength = True
args.reservoir = True
args.progressive_unfreeze = True
benchmark(args)
return
train_hyper(args)
def infer_main() -> None:
from inference import main
main()
def import_gguf_main() -> None:
from gguf_import import main
main()
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