| APP_AUTOTRAIN_USERNAME = """Please choose the user or organization who is creating the AutoTrain Project. |
| In case of non-free tier, this user or organization will be billed. |
| """ |
|
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| APP_PROJECT_NAME = """A unique name for the AutoTrain Project. |
| This name will be used to identify the project in the AutoTrain dashboard.""" |
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| APP_IMAGE_CLASSIFICATION_DATA_HELP = """The data for the Image Classification task should be in the following format: |
| - The data should be in a zip file. |
| - The zip file should contain multiple folders (the classes), each folder should contain images of a single class. |
| - The name of the folder should be the name of the class. |
| - The images must be jpeg, jpg or png. |
| - There should be at least 5 images per class. |
| - There should not be any other files in the zip file. |
| - There should not be any other folders inside the zip folder. |
| """ |
|
|
| APP_LM_TRAINING_TYPE = """There are two types of Language Model Training: |
| - generic |
| - chat |
| |
| In the generic mode, you provide a CSV with a text column which has already been formatted by you for training a language model. |
| In the chat mode, you provide a CSV with two or three text columns: prompt, context (optional) and response. |
| Context column can be empty for samples if not needed. You can also have a "prompt start" column. If provided, "prompt start" will be prepended before the prompt column. |
| |
| Please see [this](https://huggingface.co/datasets/tatsu-lab/alpaca) dataset which has both formats in the same dataset. |
| """ |
|
|
