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Code Activity

Fix typos and add Typo check GitHub Action (#483)

Browse Source 
* Fix typos

* Add a typo check action

* Fix a bug

* Changed to manual typo check currently

Ref: https://github.com/huggingface/diffusers/pull/483#pullrequestreview-1104468010

Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>

* Removed a confusing message

* Renamed "nin_shortcut" to "in_shortcut"

* Add memo about NIN

Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>
This commit is contained in:
Yuta Hayashibe
2022-09-16 22:36:51 +09:00
committed by GitHub
parent c0493723f7
commit 76d492ea49
38 changed files with 92 additions and 66 deletions
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4
examples/textual_inversion/README.md
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@@ -14,7 +14,7 @@ Colab for inference
## Running locally
### Installing the dependencies
Before running the scipts, make sure to install the library's training dependencies:
Before running the scripts, make sure to install the library's training dependencies:
```bash
pip install diffusers[training] accelerate transformers
@@ -33,7 +33,7 @@ You need to accept the model license before downloading or using the weights. In
You have to be a registered user in 🤗 Hugging Face Hub, and you'll also need to use an access token for the code to work. For more information on access tokens, please refer to [this section of the documentation](https://huggingface.co/docs/hub/security-tokens).
Run the following command to autheticate your token
Run the following command to authenticate your token
```bash
huggingface-cli login

2
examples/textual_inversion/textual_inversion.py
View File

@@ -422,7 +422,7 @@ def main():
eps=args.adam_epsilon,
)
# TODO (patil-suraj): laod scheduler using args
# TODO (patil-suraj): load scheduler using args
noise_scheduler = DDPMScheduler(
beta_start=0.00085, beta_end=0.012, beta_schedule="scaled_linear", num_train_timesteps=1000, tensor_format="pt"
)

4
examples/unconditional_image_generation/README.md
View File

@@ -4,7 +4,7 @@ Creating a training image set is [described in a different document](https://hug
### Installing the dependencies
Before running the scipts, make sure to install the library's training dependencies:
Before running the scripts, make sure to install the library's training dependencies:
```bash
pip install diffusers[training] accelerate datasets
@@ -102,7 +102,7 @@ from datasets import load_dataset
# example 1: local folder
dataset = load_dataset("imagefolder", data_dir="path_to_your_folder")
# example 2: local files (suppoted formats are tar, gzip, zip, xz, rar, zstd)
# example 2: local files (supported formats are tar, gzip, zip, xz, rar, zstd)
dataset = load_dataset("imagefolder", data_files="path_to_zip_file")
# example 3: remote files (supported formats are tar, gzip, zip, xz, rar, zstd)