OptimalScale/LMFlow
A PyTorch-based extensible toolkit for fine-tuning and serving large language models on custom datasets.
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LMFlow is a Python-based extensible toolkit for fine-tuning and inference of large foundation models. It provides a user-friendly interface for customizing training pipelines, processing datasets, and serving models for inference. Built on PyTorch with support for distributed training, it targets researchers and developers working with large language models.
Frequently asked
- What is OptimalScale/LMFlow?
- A PyTorch-based extensible toolkit for fine-tuning and serving large language models on custom datasets.
- Is LMFlow open source?
- Yes — OptimalScale/LMFlow is open source, released under the Apache-2.0 license.
- What language is LMFlow written in?
- OptimalScale/LMFlow is primarily written in Python.
- How popular is LMFlow?
- OptimalScale/LMFlow has 8.5k stars on GitHub.
- Where can I find LMFlow?
- OptimalScale/LMFlow is on GitHub at https://github.com/OptimalScale/LMFlow.