add in QLoRa Training script

README.md

@@ -5,11 +5,21 @@ colorFrom: red
 colorTo: green
 sdk: static
 pinned: false
-tags: [llama, jupyter, colab, function calling]
+tags: [llama, jupyter, colab, function calling, QLoRa, fine-tuning]
 ---
 
+# *QLoRa Training Notebook for Small Datasets*
+
+Fine-tune HuggingFace language models in Google Colab.
+- Includes a prompt loss-mask for improved performance on small datasets.
+- Includes a stop token after responses - allowing the model to provide a short reponse (e.g. a function call) and then stop.
+- Allows for fine-tuning 7B and 13B models with the free plan.
+- Allows for fine-tuning 70B models with Google Colab Pro.
+
+This script is commercially licensed and available for purchase at a price of €14.99 (or $16.49) per seat/user. [Request access here](https://buy.stripe.com/5kA5l69K52Hxf3a006). Access will be provided within 24 hours of purchase.
+
 # Function Calling Dataset
-- Commercial dataset allowing language models to be fine-tuned for function calling ([dataset here](https://huggingface.co/datasets/Trelis/function_calling_extended)).
+- Commercial dataset allowing language models to be fine-tuned for function calling ([Get access here](https://huggingface.co/datasets/Trelis/function_calling_extended)).
 - Created using only human input or Apache 2 licensed datasets (no third party commercial licensing limitations)
 - Models trained with this dataset:
 - - [Llama-2-7B](https://huggingface.co/Trelis/Llama-2-7b-chat-hf-function-calling) - repo includes Google Colab notebook