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Ray 3.0.0.dev0
Welcome to Ray!
Ray
Overview
Getting Started
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Use Cases
Example Gallery
Ecosystem
Ray Core
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Ray Train
Key Concepts
Distributed PyTorch
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Ray Train Internals
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Ray Train API
ray.train.trainer.BaseTrainer
ray.train.data_parallel_trainer.DataParallelTrainer
ray.train.DataConfig
ray.train.gbdt_trainer.GBDTTrainer
ray.train.trainer.BaseTrainer.fit
ray.train.trainer.BaseTrainer.setup
ray.train.trainer.BaseTrainer.preprocess_datasets
ray.train.trainer.BaseTrainer.training_loop
ray.train.trainer.BaseTrainer.as_trainable
ray.train.backend.Backend
ray.train.backend.BackendConfig
ray.train.context.TrainContext
ray.train.get_context
ray.train.get_dataset_shard
ray.train.report
ray.train.Checkpoint
ray.train.get_context
ray.train.context.TrainContext
ray.train.torch.TorchTrainer
ray.train.torch.TorchConfig
ray.train.torch.TorchCheckpoint
ray.train.torch.prepare_model
ray.train.torch.prepare_optimizer
ray.train.torch.prepare_data_loader
ray.train.torch.get_device
ray.train.torch.accelerate
ray.train.torch.backward
ray.train.torch.enable_reproducibility
ray.train.lightning.LightningTrainer
ray.train.lightning.LightningConfigBuilder
ray.train.lightning.LightningCheckpoint
ray.train.lightning.LightningPredictor
ray.train.tensorflow.TensorflowTrainer
ray.train.tensorflow.TensorflowConfig
ray.train.tensorflow.TensorflowCheckpoint
ray.train.tensorflow.prepare_dataset_shard
ray.train.horovod.HorovodTrainer
ray.train.horovod.HorovodConfig
ray.train.xgboost.XGBoostTrainer
ray.train.xgboost.XGBoostCheckpoint
ray.train.lightgbm.LightGBMTrainer
ray.train.lightgbm.LightGBMCheckpoint
ray.train.huggingface.TransformersTrainer
ray.train.huggingface.TransformersCheckpoint
ray.train.huggingface.TransformersCheckpoint.__init__
ray.train.huggingface.TransformersCheckpoint.as_directory
ray.train.huggingface.TransformersCheckpoint.from_bytes
ray.train.huggingface.TransformersCheckpoint.from_checkpoint
ray.train.huggingface.TransformersCheckpoint.from_dict
ray.train.huggingface.TransformersCheckpoint.from_directory
ray.train.huggingface.TransformersCheckpoint.from_model
ray.train.huggingface.TransformersCheckpoint.from_uri
ray.train.huggingface.TransformersCheckpoint.get_internal_representation
ray.train.huggingface.TransformersCheckpoint.get_model
ray.train.huggingface.TransformersCheckpoint.get_preprocessor
ray.train.huggingface.TransformersCheckpoint.get_tokenizer
ray.train.huggingface.TransformersCheckpoint.get_training_arguments
ray.train.huggingface.TransformersCheckpoint.set_preprocessor
ray.train.huggingface.TransformersCheckpoint.to_bytes
ray.train.huggingface.TransformersCheckpoint.to_dict
ray.train.huggingface.TransformersCheckpoint.to_directory
ray.train.huggingface.TransformersCheckpoint.to_uri
ray.train.huggingface.TransformersCheckpoint.path
ray.train.huggingface.TransformersCheckpoint.uri
ray.train.huggingface.AccelerateTrainer
ray.train.sklearn.SklearnTrainer
ray.train.sklearn.SklearnCheckpoint
ray.train.mosaic.MosaicTrainer
ray.train.trainer.BaseTrainer.restore
ray.train.data_parallel_trainer.DataParallelTrainer.restore
Ray Tune
Ray Serve
Ray RLlib
More Libraries
Ray Clusters
Monitoring and Debugging
References
Developer Guides
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.rst
.pdf
ray.train.huggingface.TransformersCheckpoint.get_model
ray.train.huggingface.TransformersCheckpoint.get_model
#
TransformersCheckpoint.
get_model
(
model
:
Union
[
Type
[
transformers.modeling_utils.PreTrainedModel
]
,
torch.nn.modules.module.Module
]
,
**
pretrained_model_kwargs
)
→
Union
[
transformers.modeling_utils.PreTrainedModel
,
torch.nn.modules.module.Module
]
[source]
#
Retrieve the model stored in this checkpoint.