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Installation
Dataset Preparation
Training large language models in xlstm-jax
Configuring Experiments with Hydra
Distributed Training
API Reference
xlstm_jax
xlstm_jax.common_types
xlstm_jax.configs
xlstm_jax.dataset
xlstm_jax.dataset.batch
xlstm_jax.dataset.configs
xlstm_jax.dataset.grain_batch_rampup
xlstm_jax.dataset.grain_data_processing
xlstm_jax.dataset.grain_iterator
xlstm_jax.dataset.grain_transforms
xlstm_jax.dataset.hf_tokenizer
xlstm_jax.dataset.input_pipeline_interface
xlstm_jax.dataset.lmeval_dataset
xlstm_jax.dataset.lmeval_pipeline
xlstm_jax.dataset.multihost_dataloading
xlstm_jax.dataset.synthetic_dataloading
xlstm_jax.define_hydra_schemas
xlstm_jax.distributed
xlstm_jax.distributed.array_utils
xlstm_jax.distributed.data_parallel
xlstm_jax.distributed.mesh_utils
xlstm_jax.distributed.pipeline_parallel
xlstm_jax.distributed.single_gpu
xlstm_jax.distributed.tensor_parallel
xlstm_jax.distributed.xla_utils
xlstm_jax.import_utils
xlstm_jax.kernels
xlstm_jax.kernels.kernel_utils
xlstm_jax.kernels.mlstm_chunkwise
xlstm_jax.kernels.mlstm_recurrent
xlstm_jax.kernels.stride_utils
xlstm_jax.main_train
xlstm_jax.models
xlstm_jax.models.configs
xlstm_jax.models.llama
xlstm_jax.models.shared
xlstm_jax.models.xlstm_clean
xlstm_jax.models.xlstm_parallel
xlstm_jax.models.xlstm_pytorch
xlstm_jax.resume_training
xlstm_jax.start_training
xlstm_jax.train_init_fns
xlstm_jax.trainer
xlstm_jax.trainer.base
xlstm_jax.trainer.callbacks
xlstm_jax.trainer.data_module
xlstm_jax.trainer.llm
xlstm_jax.trainer.logger
xlstm_jax.trainer.metrics
xlstm_jax.trainer.optimizer
xlstm_jax.utils
xlstm_jax.utils.error_logging_utils
xlstm_jax.utils.model_param_handling
xlstm_jax.utils.pytree_utils
lmeval_extended_evaluation
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