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optformer

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# OptFormer Project: Research in Language Modeling for Optimization

## Codebase Organization
This codebase is organized by general-purpose library folders and specific
projects:

### General-Purpose Libraries

* [**Common Imports**](https://github.com/google-research/optformer/tree/main/optformer/common)
* [**T5X Modules**](https://github.com/google-research/optformer/tree/main/optformer/t5x)
* [**PAX Modules**](https://github.com/google-research/optformer/tree/main/optformer/pax)

### Optimization API Wrappers

* [**Vizier**](https://github.com/google-research/optformer/tree/main/optformer/vizier)
* [**PyGlove**](https://github.com/google-research/optformer/tree/main/optformer/pyglove)

### Specific Papers and Projects

* [**Original OptFormer (Chen et al., 2022)**](https://github.com/google-research/optformer/tree/main/optformer/original)
* [**OmniPred (Song et al., 2024)**](https://github.com/google-research/optformer/tree/main/optformer/omnipred)
* [**Understanding LLM Embeddings (Tang et al., 2024)**](https://github.com/google-research/optformer/blob/main/optformer/t5x/embedders.py)
* [**Embed-then-Regress (Nguyen et al., 2024)**](https://github.com/google-research/optformer/tree/main/optformer/embed_then_regress)
* [**Decoding-based Regression (Song and Bahri, 2025)**](https://github.com/google-research/optformer/tree/main/optformer/decoding_regression)

**Disclaimer:** This is not an officially supported Google product.

optformer

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