# ChemLactica

## Docs

- [Introduction to ChemLactica](https://mintlify.wiki/YerevaNN/ChemLactica/introduction.md): Large language models for small molecule generation and optimization
- [Installation](https://mintlify.wiki/YerevaNN/ChemLactica/installation.md): Set up ChemLactica with conda and install all required dependencies
- [Quick start](https://mintlify.wiki/YerevaNN/ChemLactica/quickstart.md): Generate optimized molecules in minutes with ChemLactica
- [Model Architectures](https://mintlify.wiki/YerevaNN/ChemLactica/concepts/models.md): Overview of ChemLactica and Chemma model architectures and pre-trained models
- [SMILES Format](https://mintlify.wiki/YerevaNN/ChemLactica/concepts/smiles-format.md): Understanding SMILES notation for molecular representation in ChemLactica
- [Molecular Properties](https://mintlify.wiki/YerevaNN/ChemLactica/concepts/molecular-properties.md): Comprehensive guide to molecular properties calculated and used by ChemLactica models
- [Training Data](https://mintlify.wiki/YerevaNN/ChemLactica/concepts/training-data.md): Overview of the PubChem training corpus and data format used for ChemLactica models
- [Pretraining Models](https://mintlify.wiki/YerevaNN/ChemLactica/training/pretraining.md): Learn how to pretrain ChemLactica models from scratch or continue training
- [Fine-tuning](https://mintlify.wiki/YerevaNN/ChemLactica/training/fine-tuning.md): Fine-tune ChemLactica models for specific downstream tasks
- [Rejection Sampling](https://mintlify.wiki/YerevaNN/ChemLactica/training/rejection-sampling.md): Fine-tune models using rejection sampling for molecular optimization
- [Training Configuration](https://mintlify.wiki/YerevaNN/ChemLactica/training/configuration.md): Comprehensive guide to ChemLactica training configuration options
- [Molecular Optimization Overview](https://mintlify.wiki/YerevaNN/ChemLactica/optimization/overview.md): Learn how ChemLactica's genetic-like optimization algorithm achieves state-of-the-art results on molecular optimization benchmarks
- [Designing Custom Oracles](https://mintlify.wiki/YerevaNN/ChemLactica/optimization/oracle-design.md): Learn how to implement oracle functions to evaluate and guide molecular optimization
- [Optimization Algorithm](https://mintlify.wiki/YerevaNN/ChemLactica/optimization/optimization-algorithm.md): Understand how ChemLactica's genetic-like optimization algorithm works under the hood
- [Hyperparameter Configuration](https://mintlify.wiki/YerevaNN/ChemLactica/optimization/hyperparameters.md): Configure the optimization algorithm with YAML files for your specific use case
- [Complete Examples](https://mintlify.wiki/YerevaNN/ChemLactica/optimization/examples.md): Working examples of molecular optimization with ChemLactica for various objectives
- [Molecule Generation](https://mintlify.wiki/YerevaNN/ChemLactica/generation/molecule-generation.md): Generate molecules using ChemLactica models with conditional prompts
- [Prompt Format](https://mintlify.wiki/YerevaNN/ChemLactica/generation/prompting.md): Format prompts with molecular properties and similarity constraints for conditional generation
- [Sampling Strategies](https://mintlify.wiki/YerevaNN/ChemLactica/generation/sampling-strategies.md): Configure sampling parameters to control molecule generation quality and diversity
- [Building Custom Oracles](https://mintlify.wiki/YerevaNN/ChemLactica/guides/custom-oracle.md): Step-by-step guide to creating custom oracle functions for molecule optimization
- [Property Prediction Fine-Tuning](https://mintlify.wiki/YerevaNN/ChemLactica/guides/property-prediction.md): Fine-tune ChemLactica models for molecular property prediction tasks
- [Running Benchmarks](https://mintlify.wiki/YerevaNN/ChemLactica/guides/benchmarking.md): Evaluate and compare ChemLactica models on molecular generation and optimization tasks
- [Tokenization](https://mintlify.wiki/YerevaNN/ChemLactica/guides/tokenization.md): Understanding ChemLactica's tokenizer, special tokens, and molecular representation
- [optimize()](https://mintlify.wiki/YerevaNN/ChemLactica/api/optimization.md): Main optimization function for molecular generation and fine-tuning
- [Utility Classes](https://mintlify.wiki/YerevaNN/ChemLactica/api/utils.md): Core data structures for molecular optimization
- [Metrics](https://mintlify.wiki/YerevaNN/ChemLactica/api/metrics.md): Evaluation metrics for molecular optimization
- [train()](https://mintlify.wiki/YerevaNN/ChemLactica/api/train.md): Main training function for model training and fine-tuning
- [CustomTrainer](https://mintlify.wiki/YerevaNN/ChemLactica/api/custom-trainer.md): Custom trainer classes and training arguments
- [Dataset Functions](https://mintlify.wiki/YerevaNN/ChemLactica/api/datasets.md): Dataset loading and preparation utilities
- [generate()](https://mintlify.wiki/YerevaNN/ChemLactica/api/generation.md): Generate molecules from prompts using ChemLactica models
- [Rejection sampling](https://mintlify.wiki/YerevaNN/ChemLactica/api/rejection-sampling.md): API reference for rejection sampling fine-tuning

## OpenAPI Specs

- [openapi](https://mintlify.wiki/YerevaNN/ChemLactica/api-reference/openapi.json)


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