renaming

src/together/cli/api/finetune.py

@@ -9,7 +9,7 @@
 from tabulate import tabulate
 
 from together import Together
-from together.cli.api.utils import AUTO_INT
+from together.cli.api.utils import INT_WITH_MAX
 from together.utils import finetune_price_to_dollars, log_warn, parse_timestamp
 from together.types.finetune import DownloadCheckpointType, FinetuneTrainingLimits
 
@@ -46,7 +46,7 @@ def fine_tuning(ctx: click.Context) -> None:
 @click.option(
     "--n-checkpoints", type=int, default=1, help="Number of checkpoints to save"
 )
-@click.option("--batch-size", type=AUTO_INT, default="max", help="Train batch size")
+@click.option("--batch-size", type=INT_WITH_MAX, default="max", help="Train batch size")
 @click.option("--learning-rate", type=float, default=1e-5, help="Learning rate")
 @click.option(
     "--lora/--no-lora",

src/together/cli/api/utils.py

@@ -18,4 +18,4 @@ def convert(
         self.fail("Invalid integer value: {value}")
 
 
-AUTO_INT = AutoIntParamType()
+INT_WITH_MAX = AutoIntParamType()

src/together/resources/finetune.py

@@ -58,7 +58,7 @@ def create(
             n_evals (int, optional): Number of evaluation loops to run. Defaults to 0.
             n_checkpoints (int, optional): Number of checkpoints to save during fine-tuning.
                 Defaults to 1.
-            batch_size (int, optional): Batch size for fine-tuning. Defaults to auto.
+            batch_size (int, optional): Batch size for fine-tuning. Defaults to max.
             learning_rate (float, optional): Learning rate multiplier to use for training
                 Defaults to 0.00001.
             lora (bool, optional): Whether to use LoRA adapters. Defaults to True.