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chore: Fix typos in docs and examples (#36524)

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Fix typos in docs and examples

Signed-off-by: co63oc <co63oc@users.noreply.github.com>
This commit is contained in:
co63oc
2025-03-04 21:47:41 +08:00
committed by GitHub
parent 84f0186e89
commit 37508816d6
38 changed files with 50 additions and 50 deletions
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docs/source/en/deepspeed.md
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@@ -840,7 +840,7 @@ Unless you have a lot of free CPU memory, fp32 weights shouldn't be saved during
<hfoptions id="save">
<hfoption id="offline">
DeepSpeed provies a [zero_to_fp32.py](https://github.com/microsoft/DeepSpeed/blob/91829476a8fd4d0d9268c03c1d56795d20a51c12/deepspeed/utils/zero_to_fp32.py#L14) script at the top-level checkpoint folder for extracting weights at any point. This is a standalone script and you don't need a config file or [`Trainer`].
DeepSpeed provides a [zero_to_fp32.py](https://github.com/microsoft/DeepSpeed/blob/91829476a8fd4d0d9268c03c1d56795d20a51c12/deepspeed/utils/zero_to_fp32.py#L14) script at the top-level checkpoint folder for extracting weights at any point. This is a standalone script and you don't need a config file or [`Trainer`].
For example, if your checkpoint folder looks like the one shown below, then you can run the following command to create and consolidate the fp32 weights from multiple GPUs into a single `pytorch_model.bin` file. The script automatically discovers the subfolder `global_step1` which contains the checkpoint.
@@ -942,7 +942,7 @@ import deepspeed
ds_config = {...}
# must run before instantiating the model to detect zero 3
dschf = HfDeepSpeedConfig(ds_config) # keep this object alive
# randomly intialize model weights
# randomly initialize model weights
config = AutoConfig.from_pretrained("openai-community/gpt2")
model = AutoModel.from_config(config)
engine = deepspeed.initialize(model=model, config_params=ds_config, ...)