AutoML (Automated Machine Learning)
AutoML (Automated Machine Learning) is the automation of the end-to-end pipeline of applying machine learning to real-world data, replacing manual trial and error with a formal search over data preprocessing…
Training & Optimization
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Axolotl
Axolotl is a free and open source framework for fine-tuning and post-training large language models, written in Python and driven entirely by a single YAML configuration file.
Fully Sharded Data Parallel (FSDP)
Fully Sharded Data Parallel (FSDP) is a distributed training technique implemented in PyTorch that shards a model's parameters, gradients, and optimizer states across data-parallel workers, allowing models…
HuggingFace PEFT
PEFT (Parameter-Efficient Fine-Tuning) is an open-source Python library from Hugging Face that adapts large pretrained models to new tasks by training only a small set of added or selected parameters, often…
LLaMA-Factory
LLaMA-Factory is an open-source unified framework for the efficient fine-tuning of large language models (LLMs) and vision-language models (VLMs).
Unsloth
Unsloth is an open-source Python library that fine-tunes large language models up to two times faster while using up to 70 percent less GPU memory and, in its own words, with "no accuracy loss".
torch.compile
torch.compile is the just-in-time graph capture and compilation feature introduced in PyTorch 2.0, a release first announced at the PyTorch Conference on December 2, 2022 and shipped as a stable version on…