1. https://keras.io/guides/custom_train_step_in_tensorflow/
2. https://keras.io/guides/writing_a_custom_training_loop_in_tensorflow/
3. https://keras.io/guides/making_new_layers_and_models_via_subclassing/
4. https://keras.io/guides/writing_your_own_callbacks/
5. https://keras.io/guides/distribution/
6. https://keras.io/guides/distributed_training_with_tensorflow/
7. https://keras.io/guides/custom_train_step_in_torch/
8. https://keras.io/guides/writing_a_custom_training_loop_in_torch/
9. https://keras.io/guides/distributed_training_with_torch/

.

1. https://keras.io/guides/keras_cv/generate_images_with_stable_diffusion/
2. https://keras.io/examples/vision/super_resolution_sub_pixel/
3. https://keras.io/examples/vision/edsr/
4. https://keras.io/examples/generative/ddim/
5. https://keras.io/examples/generative/random_walks_with_stable_diffusion

.

1. https://github.com/huggingface/peft/blob/main/README.md
2. https://github.com/huggingface/peft/blob/main/docs/source/quicktour.md
3. https://github.com/huggingface/peft/blob/main/docs/source/conceptual_guides/adapter.md
4. https://github.com/huggingface/peft/blob/main/docs/source/conceptual_guides/ia3.md
5. https://github.com/huggingface/peft/blob/main/docs/source/conceptual_guides/oft.md
6. https://github.com/huggingface/peft/blob/main/docs/source/developer_guides/lora.md
7. https://github.com/huggingface/peft/blob/main/docs/source/task_guides/lora_based_methods.md
8. https://github.com/huggingface/peft/blob/main/docs/source/task_guides/prompt_based_methods.md
9. https://github.com/huggingface/peft/blob/main/docs/source/tutorial/peft_integrations.md
10. https://github.com/huggingface/peft/blob/main/docs/source/tutorial/peft_model_config.md

.

1. https://www.kaggle.com/code/awsaf49/kaggle-qa-with-gemma-kerasnlp-starter
2. https://www.kaggle.com/code/wlifferth/starter-notebook-generating-more-data-with-gemma
3. https://www.kaggle.com/code/awsaf49/prompt-recovery-with-gemma-kerasnlp-starter
4. https://www.kaggle.com/code/nilaychauhan/fine-tune-gemma-models-in-keras-using-lora
5. https://keras.io/examples/nlp/parameter_efficient_finetuning_of_gpt2_with_lora/

.

1. https://stats.stackexchange.com/questions/61783/bias-and-variance-in-leave-one-out-vs-k-fold-cross-validation
2. https://stats.stackexchange.com/questions/280665/variance-of-k-fold-cross-validation-estimates-as-fk-what-is-the-role-of
3. https://stats.stackexchange.com/questions/365224/cross-validation-and-confidence-interval-of-the-true-error
4. https://stats.stackexchange.com/questions/61546/optimal-number-of-folds-in-k-fold-cross-validation-is-leave-one-out-cv-always
5. https://stats.stackexchange.com/questions/27730/choice-of-k-in-k-fold-cross-validation
6. https://stats.stackexchange.com/questions/61783/variance-and-bias-in-cross-validation-why-does-leave-one-out-cv-have-higher-var
7. https://stats.stackexchange.com/questions/178388/high-variance-of-leave-one-out-cross-validation
8. https://stats.stackexchange.com/questions/90902/why-is-leave-one-out-cross-validation-loocv-variance-about-the-mean-estimate-f