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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
        • bionemo-amplify
        • bionemo-core
        • bionemo-esm2
        • bionemo-evo2
        • bionemo-example-model
        • bionemo-fw
        • bionemo-geneformer
        • bionemo-llm
        • bionemo-moco
        • bionemo-noodles
        • bionemo-scdl
        • bionemo-size-aware-batching
        • bionemo-testing
        • bionemo-webdatamodule
      • Recipes
        • Models
            • AMPLIFY Optimized with NVIDIA TransformerEngine
            • ESM-2 Optimized with NVIDIA TransformerEngine
            • Geneformer Implemented with Transformer Engine
            • 🚧 Llama-3.1 Optimized with NVIDIA TransformerEngine
        • Recipes
            • Codonfm ptl te
            • TransformerEngine-accelerated ESM-2 training with Hugging Face Trainer
            • TransformerEngine-accelerated ESM-2 training with native PyTorch training loop
            • PEFT Fine-tuning with TransformerEngine-accelerated ESM-2
            • Geneformer native te mfsdp fp8
            • BioNeMo-Vision: Training a VisionTransformer (ViT) with Megatron-FSDP and TransformerEngine
        • ESM-2
          • Fine tuning tutorial
          • Zero-shot prediction of BRCA1 variant effects with Evo 2
          • Geneformer Cell Type Classification Benchmark
          • Geneformer gene embeddings extraction and building a gene co-expression/regulation network (GRN)
          • BioNeMo - Geneformer inferencing for single cell downstream tasks
          • 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
              • Api
              • Data
                • Api
                • Load
                • Multi epoch dataset
                • Permute
                • Resamplers
                • Resource
                • Config
                • Batching utils
                • Dtypes
                • Random utils
                • Subprocess utils
              • Data
                • Fasta dataset
                • Preprocess
                • Sharded Eden DataLoader Implementation
                • Tokenizer
                • Transcript extraction
                • Llama
                • Mamba
                • Peft
                • Infer
                • Predict
                • Train
                • Utils
                • Callbacks
                • Config
                • Checkpoint
                  • Convert checkpoint model parallel evo2
                  • Convert to nemo
                  • Convert zero3 to zero1
                  • Evo2 remove optimizer
                  • Nemo2 to hf
                  • Params
                  • Zero3 conversion lib
                  • Callbacks
                  • Embedding variance
                • Lightning basic
                • Finetune mnist
                • Predict mnist
                • Pretrain mnist
              • Api
                • Preprocess
                  • Datamodule
                  • Dataset
                  • Preprocess
                  • Utils
                • Finetune token regressor
                • Config models
                • Main
                • Recipes
              • Scripts
                • Infer geneformer
                • Train geneformer
                • Celltype classification bench
                  • Bench
                  • Download
                • Gene tokenizer
                • Callbacks
              • Api
              • Lightning
              • Train
                • Collate
                • Datamodule
                • Label2id tokenizer
                • Masking
                • Types
                • Config
                • Layers
                • Loss
                • Lr scheduler
                  • Lightning
                  • Model
                  • Testing utils
                  • Transformer specs
                • Config models
                • Callbacks
                • Datamodule utils
                • Iomixin utils
                • Logger utils
                • Megatron utils
                • Remote
                • Weight 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
                • 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
              • Assert optimizer grads match
              • Callbacks
              • Lightning
              • Megatron dataset compatibility
              • Megatron parallel state utils
              • Subprocess utils
              • Tensorboard
              • Testing callbacks
              • Torch
              • Utils
                • Esm2
                • Fasta
                • Load
                • Resource
                • Mode
                • Stop and go
              • Datamodule
              • Utils
    • Models
      • Amplify
      • Evo2
      • Geneformer
      • ESM 2
        • Pre-trained Checkpoints

    SUMMARY

    • bionemo-amplify
    • bionemo-core
    • bionemo-esm2
    • bionemo-evo2
    • bionemo-example-model
    • bionemo-fw
    • bionemo-geneformer
    • bionemo-llm
    • bionemo-moco
    • bionemo-noodles
    • bionemo-scdl
    • bionemo-size-aware-batching
    • bionemo-testing
    • bionemo-webdatamodule
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