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README.md

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-title: Lora Instruction Training
+title: SLM Instruction Tuning using Unsloth
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 license: apache-2.0
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-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# SLM Instruction Tuning using Unsloth
+
+### What?
+
+This Gradio app is a simple interface to access [unsloth AI's](https://github.com/unslothai) fine-tuning methods but leveraging the A100 GPUs provided by [Huggingface Spaces](https://huggingface.co/docs/hub/en/spaces-overview). This outputs of this fine-tuning will be instruction tuned LoRA weights that will be uploaded into your personal huggingface models repository.
+
+[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
+
+### Why?
+
+The goal of this demo is to show how you can tune your own language models leveraging industry standard compute and fine tuning methods using a simple point-and-click UI.
+
+In addition, compute, even on Google Colab's free tier is tight even with a T4 and rate limits are uncertain. This makes the use of the A100s on this demo useful for a small added boost to compute performance. For those looking to reduce the costs associated with training datasets can pull down the spaces repository to train their models at speed for $9 on The Huggingface Pro License.
+
+This is a demo and not a production application. This application is subject a demand queue.
+
+### How?
+
+Just start by following the guide below:
+
+1) Flip to the Train Model tab at the top.
+2) Populate your username, repository, token, and model details
+3) Upload data from transformers or your local jsonl file. Please view [this guide](https://platform.openai.com/docs/guides/fine-tuning/preparing-your-dataset) for best practices.
+4) Eat a snack and wait as you train the model.
+
+### Coming soon!
+
+- More models and added flexibility with guardrails on hyperparameter tuning.
+- Downloads for a [WandB](https://wandb.ai/home) logger for training monitoring.
+
+### Other resources.
+
+- [Unsloth's notebooks](https://colab.research.google.com/drive/1hhdhBa1j_hsymiW9m-WzxQtgqTH_NHqi?usp=sharing) to look at what is going on under the hood.
+
+