Merge pull request red-hat-data-services#64 from MStokluska/Fine-tuning-3.4GA-examples

Update for 3.4 and refactor to simplify

Author: MStokluska

examples/fine-tuning/README.md

@@ -16,11 +16,11 @@ For detailed algorithm documentation and configuration options, see the upstream
 
 There are three ways to run fine tuning examples:
 
-1. **Interactive Notebooks (Single Node Fine Tuning)**
-2. **Training Jobs (Distributed Fine Tuning with Kubeflow Trainer)**
+1. **Interactive (single node fine tuning)**
+2. **Distributed (distributed fine tuning with Kubeflow Trainer)**
 3. **Pipeline mode (automated training, model evaluation, and registration with Kubeflow Pipelines)**
 
-### Interactive Notebooks (Single Node Fine Tuning)
+### Interactive (single node fine tuning)
 
 **What it is**
 
@@ -49,13 +49,13 @@ Training runs directly inside a **single Workbench pod** (your notebook environm
 
 **Learn more**
 
-- [SFT fine-tuning example](training-hub/sft/README.md)
+- [SFT fine-tuning example](sft/README.md)
 - [OSFT fine-tuning example](osft/README.md)
-- [LORA fine-tuning example](lora/README.md)
+- [LoRA fine-tuning example](lora/README.md)
 
 ---
 
-### Training Jobs (Distributed Fine Tuning with Kubeflow Trainer)
+### Distributed (distributed fine tuning with Kubeflow Trainer)
 
 **What it is**
 
@@ -90,8 +90,9 @@ Training is offloaded to **dedicated training pods** managed by **Kubeflow Train
 
 **Learn more**
 
-- [SFT fine-tuning example](training-hub/sft/README.md)
+- [SFT fine-tuning example](sft/README.md)
 - [OSFT fine-tuning example](osft/README.md)
+- [LoRA fine-tuning example](lora/README.md)
 
 ---