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BioNeMo
SUMMARY
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    NVIDIA/bionemo-framework
    • Home
    • BioNeMo Framework
    • Models
    NVIDIA/bionemo-framework
    • Home
        • Overview
          • NeMo2
          • Megatron Dataset Considerations
        • Release Notes
        • Hardware and Software Prerequisites
        • Access and Startup
        • Initialization Guide
        • Development
        • Training Models
        • Using SLURM
      • Recipes
        • Models
          • Models Directory
          • Amplify
          • Esm2
          • Geneformer
            • Model readme
          • Llama3
          • Mixtral
          • Qwen
        • Recipes
          • Recipes Directory
          • Context Parallelism
          • Codonfm native te
          • Codonfm ptl te
              • 0-Zero-Shot-Mutation-Cancer-Hotspot
              • Mutation Datasets Preprocessing
              • 1-Zero-Shot-Mutation-Variant-DDD-ASD
              • 2-Zero-Shot-Mutation-Variant-Clinvar-Alphamissense
              • 3-Zero-Shot-Mutation-Variant-Clinvar-Synonymous
              • Tutorial 4: RiboNN Translation Efficiency Prediction with Encodon
              • Tutorial 5: mRFP Expression Prediction with Encodon
              • Tutorial 6: mRNA Stability Prediction with Encodon
          • Eden megatron
          • Esm2 accelerate te
          • Esm2 native te
          • Esm2 peft te
          • Evo2 megatron
              • Fine tuning tutorial
              • Zero-shot prediction of BRCA1 variant effects with Evo 2
              • Configs
          • Fp8 analysis
          • Geneformer native te mfsdp fp8
          • Llama3 native te
          • Opengenome2 llama native te
            • OpenGenome2 Metagenome Dataset: Sharding, Shuffling, and Tokenization in the LlaMA 3 Recipe
          • Vit
        • bionemo-core
        • bionemo-moco
        • bionemo-noodles
        • bionemo-recipeutils
        • bionemo-scdl
        • bionemo-scspeedtest
        • bionemo-size-aware-batching
        • bionemo-webdatamodule
            • Fine tuning tutorial
            • Zero-shot prediction of BRCA1 variant effects with Evo 2
            • Configs
            • 0-Zero-Shot-Mutation-Cancer-Hotspot
            • Mutation Datasets Preprocessing
            • 1-Zero-Shot-Mutation-Variant-DDD-ASD
            • 2-Zero-Shot-Mutation-Variant-Clinvar-Alphamissense
            • 3-Zero-Shot-Mutation-Variant-Clinvar-Synonymous
            • Tutorial 4: RiboNN Translation Efficiency Prediction with Encodon
            • Tutorial 5: mRFP Expression Prediction with Encodon
            • Tutorial 6: mRNA Stability Prediction with Encodon
            • Building Generative Models for Continuous Data via Continuous Interpolants
            • Building Generative Models for Continuous Data via Continuous Interpolants
            • Building Generative Models for Continuous Data via Continuous Interpolants
            • Building Generative Models for Discrete Data via Discrete Interpolants
            • Entropic Flow Matching for Optimal Time Scheduling
            • Optimal Transport Samplers Tutorial
            • Example notebook
      • Data Sets
        • CELLxGENE
        • UniProt Dataset
        • Code Review
        • Contributing Guidelines
        • Sub package dependency graph
        • Writing Documentation
          • Jupyter Notebook Support
          • MkDocs
        • Frequently Asked Questions
        • API reference
              • Data
                • Api
                • Load
                • Multi epoch dataset
                • Permute
                • Resamplers
                • Resource
                • Batching utils
                • Dtypes
                • Random utils
                • Subprocess utils
                  • Distribution
                    • Gaussian
                    • Harmonic
                    • Utils
                    • Custom
                    • Mask
                    • Uniform
                  • Beta
                  • Distribution
                  • Logit normal
                  • Uniform
                  • Utils
                • Base interpolant
                • Batch augmentation
                    • Continuous flow matching
                    • Vdm
                      • Augmentation types
                      • Equivariant ot sampler
                      • Kabsch augmentation
                      • Ot sampler
                    • Discrete flow matching
                    • Mdlm
                  • Utils
                    • Ddpm
                    • D3pm
                • Inference time schedules
                • Utils
                  • Continuous noise transforms
                  • Continuous snr transforms
                  • Discrete noise schedules
                • Parallel test utils
              • Nvfaidx
                • Remove optimizer
                  • Sharded dataset
                  • Utils
                • Collation
                • Fasta to jsonl
                • Single cell row dataset
                • Load
                • Row feature index
                • Single cell collection
                • Single cell memmap dataset
                • Header
                • Headerutil
                • Magic
                • Version
                • Convert h5ad to scdl
                • Async worker queue
                • Filecopyutil
                • Memmap utils
                • Scdl constants
                • Torch dataloader utils
              • Benchmark
              • Common
              • Sampler
              • Utils
              • Datamodule
              • Utils
    • Models
      • Amplify
      • Evo2
      • Geneformer
      • ESM 2
        • Pre-trained Checkpoints

    SUMMARY

    • bionemo-core
    • bionemo-moco
    • bionemo-noodles
    • bionemo-recipeutils
    • bionemo-scdl
    • bionemo-scspeedtest
    • bionemo-size-aware-batching
    • bionemo-webdatamodule
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