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Fix typos (#12705)

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This commit is contained in:
omahs
2026-01-10 20:11:15 +01:00
committed by GitHub
parent 4ac2b4a521
commit 5b202111bf
8 changed files with 11 additions and 11 deletions
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4
examples/cogvideo/train_cogvideox_image_to_video_lora.py
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@@ -149,13 +149,13 @@ def get_args():
"--validation_prompt",
type=str,
default=None,
help="One or more prompt(s) that is used during validation to verify that the model is learning. Multiple validation prompts should be separated by the '--validation_prompt_seperator' string.",
help="One or more prompt(s) that is used during validation to verify that the model is learning. Multiple validation prompts should be separated by the '--validation_prompt_separator' string.",
)
parser.add_argument(
"--validation_images",
type=str,
default=None,
help="One or more image path(s) that is used during validation to verify that the model is learning. Multiple validation paths should be separated by the '--validation_prompt_seperator' string. These should correspond to the order of the validation prompts.",
help="One or more image path(s) that is used during validation to verify that the model is learning. Multiple validation paths should be separated by the '--validation_prompt_separator' string. These should correspond to the order of the validation prompts.",
)
parser.add_argument(
"--validation_prompt_separator",

2
examples/cogvideo/train_cogvideox_lora.py
View File

@@ -140,7 +140,7 @@ def get_args():
"--validation_prompt",
type=str,
default=None,
help="One or more prompt(s) that is used during validation to verify that the model is learning. Multiple validation prompts should be separated by the '--validation_prompt_seperator' string.",
help="One or more prompt(s) that is used during validation to verify that the model is learning. Multiple validation prompts should be separated by the '--validation_prompt_separator' string.",
)
parser.add_argument(
"--validation_prompt_separator",

2
examples/research_projects/onnxruntime/text_to_image/README.md
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@@ -4,7 +4,7 @@ The `train_text_to_image.py` script shows how to fine-tune stable diffusion mode
___Note___:
___This script is experimental. The script fine-tunes the whole model and often times the model overfits and runs into issues like catastrophic forgetting. It's recommended to try different hyperparamters to get the best result on your dataset.___
___This script is experimental. The script fine-tunes the whole model and often times the model overfits and runs into issues like catastrophic forgetting. It's recommended to try different hyperparameters to get the best result on your dataset.___
## Running locally with PyTorch

2
examples/research_projects/sdxl_flax/sdxl_single.py
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@@ -18,7 +18,7 @@ cc.initialize_cache("/tmp/sdxl_cache")
NUM_DEVICES = jax.device_count()
# 1. Let's start by downloading the model and loading it into our pipeline class
# Adhering to JAX's functional approach, the model's parameters are returned seperatetely and
# Adhering to JAX's functional approach, the model's parameters are returned separately and
# will have to be passed to the pipeline during inference
pipeline, params = FlaxStableDiffusionXLPipeline.from_pretrained(
"stabilityai/stable-diffusion-xl-base-1.0", revision="refs/pr/95", split_head_dim=True