chunked/content_aware_chunking/_deepspeed/chunk_10.txt

-name '*json')

The DeepSpeed configuration file is passed as a path to a JSON file if you're training from the command line interface or as a nested dict object if you're using the [Trainer] in a notebook setting.

py
TrainingArguments(, deepspeed="path/to/deepspeed_config.json")

py
ds_config_dict = dict(scheduler=scheduler_params, optimizer=optimizer_params)
args = TrainingArguments(, deepspeed=ds_config_dict)
trainer = Trainer(model, args, )

DeepSpeed and Trainer parameters
There are three types of configuration parameters:

Some of the configuration parameters are shared by [Trainer] and DeepSpeed, and it can be difficult to identify errors when there are conflicting definitions.