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NeMo-RL

Table of Contents

🖥️ Environment Start

  • Run on Your Local Workstation
  • Set Up Clusters

🚀 E2E Examples

  • GRPO on DeepScaler
  • SFT on OpenMathInstruct-2

📚 Guides

  • Add New Models
  • Supervised Fine-Tuning in NeMo RL
  • Direct Preference Optimization in NeMo RL
  • An in-depth Walkthrough of GRPO in NeMo RL
  • GRPO on DeepScaler
  • Evaluation
  • DeepSeek-V3
  • Model Quirks

🐳 Containers

  • Build Docker Images

🛠️ Development

  • Test NeMo RL
  • Documentation Development
  • Debug NeMo RL Applications
  • Profile GPU with Nsys
  • Experiment with Custom vLLM
  • API Reference
    • nemo_rl
      • nemo_rl.utils
        • nemo_rl.utils.config
        • nemo_rl.utils.checkpoint
        • nemo_rl.utils.nsys
        • nemo_rl.utils.native_checkpoint
        • nemo_rl.utils.nvml
        • nemo_rl.utils.prefetch_venvs
        • nemo_rl.utils.venvs
        • nemo_rl.utils.logger
        • nemo_rl.utils.timer
      • nemo_rl.experience
        • nemo_rl.experience.rollouts
      • nemo_rl.environments
        • nemo_rl.environments.utils
        • nemo_rl.environments.math_environment
        • nemo_rl.environments.interfaces
        • nemo_rl.environments.metrics
      • nemo_rl.data
        • nemo_rl.data.eval_datasets
        • nemo_rl.data.hf_datasets
        • nemo_rl.data.datasets
        • nemo_rl.data.interfaces
        • nemo_rl.data.llm_message_utils
        • nemo_rl.data.processors
      • nemo_rl.distributed
        • nemo_rl.distributed.ray_actor_environment_registry
        • nemo_rl.distributed.model_utils
        • nemo_rl.distributed.named_sharding
        • nemo_rl.distributed.batched_data_dict
        • nemo_rl.distributed.worker_group_utils
        • nemo_rl.distributed.virtual_cluster
        • nemo_rl.distributed.worker_groups
        • nemo_rl.distributed.collectives
      • nemo_rl.algorithms
        • nemo_rl.algorithms.sft
        • nemo_rl.algorithms.utils
        • nemo_rl.algorithms.loss_functions
        • nemo_rl.algorithms.grpo
        • nemo_rl.algorithms.dpo
        • nemo_rl.algorithms.interfaces
      • nemo_rl.converters
        • nemo_rl.converters.huggingface
        • nemo_rl.converters.megatron
      • nemo_rl.models
        • nemo_rl.models.dtensor
        • nemo_rl.models.huggingface
        • nemo_rl.models.policy
        • nemo_rl.models.generation
        • nemo_rl.models.megatron
      • nemo_rl.metrics
        • nemo_rl.metrics.metrics_utils
      • nemo_rl.evals
        • nemo_rl.evals.eval
        • nemo_rl.evals.answer_parsing
      • nemo_rl.package_info

📐 Design Docs

  • Design and Philosophy
  • Padding in NeMo RL
  • Logger
  • uv in NeMo RL
  • Data Format
  • Generation Interface
  • Checkpointing with Hugging Face Models
  • Loss functions in NeMo RL
  • FSDP2 Parallel Plan
  • Training Backends
  • API Reference
  • nemo_rl
  • nemo_rl.data
  • nemo_rl.data.eval_datasets
  • nemo_rl.data.eval_datasets.aime2024

nemo_rl.data.eval_datasets.aime2024#

AIME 2024 dataset.

Module Contents#

Classes#

AIME2024Dataset

API#

class nemo_rl.data.eval_datasets.aime2024.AIME2024Dataset(
prompt_file: Optional[str] = None,
system_prompt_file: Optional[str] = None,
)[source]#

Initialization

_rekey(data: dict[str, Any])[source]#

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  • Module Contents
    • Classes
    • API
      • AIME2024Dataset
        • _rekey()
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