Add push_to_hub to the trainer (#109)

* add push_to_hub

* fix indentation

* indent again

* model_config

* allow samples to not exist

* repo creation fix

* dont show empty [] if widget doesnt exist

* dont submit the config and optimizer

* Unsafe to have tokens saved in the yaml file

* make sure to catch only the latest samples

* change name to slug

* formatting

* formatting

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Co-authored-by: multimodalart <joaopaulo.passos+multimodal@gmail.com>

config/examples/train_lora_flux_24gb.yaml

@@ -21,6 +21,10 @@ config:
         dtype: float16 # precision to save
         save_every: 250 # save every this many steps
         max_step_saves_to_keep: 4 # how many intermittent saves to keep
+        push_to_hub: false #change this to True to push your trained model to Hugging Face.
+        # You can either set up a HF_TOKEN env variable or you'll be prompted to log-in         
+#       hf_repo_id: your-username/your-model-slug
+#       hf_private: true #whether the repo is private or public
       datasets:
         # datasets are a folder of images. captions need to be txt files with the same name as the image
         # for instance image2.jpg and image2.txt. Only jpg, jpeg, and png are supported currently

config/examples/train_lora_flux_schnell_24gb.yaml

@@ -21,6 +21,10 @@ config:
         dtype: float16 # precision to save
         save_every: 250 # save every this many steps
         max_step_saves_to_keep: 4 # how many intermittent saves to keep
+        push_to_hub: false #change this to True to push your trained model to Hugging Face.
+        # You can either set up a HF_TOKEN env variable or you'll be prompted to log-in         
+#       hf_repo_id: your-username/your-model-slug
+#       hf_private: true #whether the repo is private or public        
       datasets:
         # datasets are a folder of images. captions need to be txt files with the same name as the image
         # for instance image2.jpg and image2.txt. Only jpg, jpeg, and png are supported currently