LLMForge releases

LLMForge version	Image URI	Ray version	Python version	Changelog
0.5.9	localhost:5555/anyscale/llm-forge:0.5.9	2.40.0	3.11.10	Link
0.5.8	localhost:5555/anyscale/llm-forge:0.5.8	2.38.0	3.11.10	Link
0.5.7	localhost:5555/anyscale/llm-forge:0.5.7	2.35.0	3.11.9	Link
0.5.6	localhost:5555/anyscale/llm-forge:0.5.6	2.35.0	3.11.9	Link
0.5.5	localhost:5555/anyscale/llm-forge:0.5.5	2.32.0	3.11.9	Link
0.5.4	localhost:5555/anyscale/llm-forge:0.5.4	2.32.0	3.11.9	-
0.5.3	localhost:5555/anyscale/llm-forge:0.5.3	2.32.0	3.11.9	-
0.5.2	localhost:5555/anyscale/llm-forge:0.5.2	2.32.0	3.11.9	-
0.5.1	localhost:5555/anyscale/llm-forge:0.5.1	2.31.0	3.11.9	-
0.5.0.1	localhost:5555/anyscale/llm-forge:0.5.0.1-ngmM6BdcEdhWo0nvedP7janPLKS9Cdz2	2.24.0	3.10.14	-

Changelog

Version 0.5.9

• Added experimental support for vision-language training, which supports Pixtral architecture
• Added new optimizer_config option for custom Hugging Face optimizer configurations; API Reference
• Upgraded rayturbo to 2.40
• General improvements and bug fixes

Version 0.5.8

• Added new checkpoint_and_evaluation_frequency for customizing checkpointing and evaluation cadence.
  • Resources: API Reference | Example usage
• Upgraded rayturbo to 2.38, which comes with many improvements in Ray Data
• Added support for torch.compile; API Reference
• General improvements in data preprocessing and logging

⚠️ Deprecation notice ⚠️

• The parameters checkpoint_every_n_epochs and max_num_checkpoints are deprecated and will be removed in version 0.6. Use checkpoint_and_evaluation_frequency instead.

Version 0.5.7

• Added support for Llama 3.1 and 3.2 with default configurations
• Improved checkpoint discovery for serving; storage_uri returned by anyscale.llm.model.get now contains forwarded checkpoint for LoRA. User guide
• Renamed no_gradient_checkpoint to gradient_checkpointing
• General improvements in configuration management and stability

⚠️ Deprecation notice ⚠️

• The no_gradient_checkpoint parameter is now deprecated and will be removed in version 0.6. Use gradient_checkpointing instead.

Version 0.5.6

• Upgraded to Rayturbo 2.35 with Ray Data and Ray dashboard improvements
• Added integration with Liger Kernel.
  • Resources: API Reference | Docs | Example Usage
• Added support for different fine-tuning tasks with a new task parameter:
  • Instruction tuning, ignores user messages in the loss
  • Classification, predicts only user-defined labels
  • Direct Preference Optimization, trains on preference data
  • Resources: Docs | Preference tuning end-to-end example | Classification end-to-end example
• General improvements and bug fixes

Version 0.5.5

• Added configurable support for MLflow and W&B logging.
  • Resources: API Reference | Docs | W&B Example | MLflow Example