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combine like functions

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This commit is contained in:
Dan Saunders
2025-02-28 17:47:39 +00:00
parent ed5178cd3d
commit e1bc18763a
1 changed files with 6 additions and 10 deletions
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16
src/axolotl/train.py
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@@ -345,19 +345,16 @@ def save_initial_configs(
model.config.save_pretrained(str(output_dir)) model.config.save_pretrained(str(output_dir))
def setup_badge_for_model_card(): def setup_model_card(cfg: DictDefault):
"""Set up the Axolotl badge for the model card."""
badge_markdown = """[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)"""
transformers.modelcard.AUTOGENERATED_TRAINER_COMMENT += f"\n{badge_markdown}"
def add_config_to_model_card(cfg: DictDefault):
""" """
Add the Axolotl configuration to the model card if available. Set up the Axolotl badge and add the Axolotl config to the model card if available.
Args: Args:
cfg: The configuration dictionary with path to axolotl config file cfg: The configuration dictionary with path to axolotl config file
""" """
badge_markdown = """[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)"""
transformers.modelcard.AUTOGENERATED_TRAINER_COMMENT += f"\n{badge_markdown}"
if getattr(cfg, "axolotl_config_path"): if getattr(cfg, "axolotl_config_path"):
raw_axolotl_cfg = Path(cfg.axolotl_config_path) raw_axolotl_cfg = Path(cfg.axolotl_config_path)
version = get_distribution("axolotl").version version = get_distribution("axolotl").version
@@ -460,8 +457,7 @@ def train(
setup_signal_handler(cfg, model, safe_serialization) setup_signal_handler(cfg, model, safe_serialization)
# Set up badges and config info for model card # Set up badges and config info for model card
setup_badge_for_model_card() setup_model_card(cfg)
add_config_to_model_card(cfg)
# Execute the training # Execute the training
execute_training(cfg, trainer, resume_from_checkpoint) execute_training(cfg, trainer, resume_from_checkpoint)