Merge branch 'main' into feature/length_based_batch_sampling

README.md

@@ -1,7 +1,13 @@
-# Llama 2 Fine-tuning / Inference Recipes and Examples
+# Llama 2 Fine-tuning / Inference Recipes, Examples and Demo Apps
+
+**[Update Oct. 20, 2023] We have just released a series of Llama 2 demo apps [here](./demo_apps). These apps show how to run Llama 2 locally and in the cloud to chat about data (PDF, DB, or live) and generate video summary.**
+
 
 The 'llama-recipes' repository is a companion to the [Llama 2 model](https://github.com/facebookresearch/llama). The goal of this repository is to provide examples to quickly get started with fine-tuning for domain adaptation and how to run inference for the fine-tuned models. For ease of use, the examples use Hugging Face converted versions of the models. See steps for conversion of the model [here](#model-conversion-to-hugging-face).
 
+In addition, we also provide a number of demo apps, to showcase the Llama2 usage along with other ecosystem solutions to run Llama2 locally on your mac and on cloud.
+
+
 Llama 2 is a new technology that carries potential risks with use. Testing conducted to date has not — and could not — cover all scenarios. In order to help developers address these risks, we have created the [Responsible Use Guide](https://github.com/facebookresearch/llama/blob/main/Responsible-Use-Guide.pdf). More details can be found in our research paper as well. For downloading the models, follow the instructions on [Llama 2 repo](https://github.com/facebookresearch/llama).
 
 
@@ -13,8 +19,9 @@ Llama 2 is a new technology that carries potential risks with use. Testing condu
     - [Multi GPU One Node](#multiple-gpus-one-node)
     - [Multi GPU Multi Node](#multi-gpu-multi-node)
 4. [Inference](./docs/inference.md)
-5. [Repository Organization](#repository-organization)
-6. [License and Acceptable Use Policy](#license)
+5. [Demo Apps](#demo-apps)
+6. [Repository Organization](#repository-organization)
+7. [License and Acceptable Use Policy](#license)
 
 
 
@@ -174,6 +181,17 @@ sbatch multi_node.slurm
 ```
 You can read more about our fine-tuning strategies [here](./docs/LLM_finetuning.md).
 
+# Demo Apps
+This folder contains a series of Llama2-powered apps:
+* Quickstart Llama deployments and basic interactions with Llama
+  1. Llama on your Mac and ask Llama general questions
+  2. Llama on Google Colab
+  3. Llama on Cloud and ask Llama questions about unstructured data in a PDF
+
+* Specialized Llama use cases:
+  1. Ask Llama to summarize a video content
+  2. Ask Llama questions about structured data in a DB
+  3. Ask Llama questions about live data on the web
 
 # Repository Organization
 This repository is organized in the following way:
@@ -184,6 +202,8 @@ This repository is organized in the following way:
 
 [datasets](src/llama_recipes/datasets/): Contains individual scripts for each dataset to download and process. Note: Use of any of the datasets should be in compliance with the dataset's underlying licenses (including but not limited to non-commercial uses)
 
+[demo_apps](./demo_apps) contains a series of Llama2-powered apps, from quickstart deployments to how to ask Llama questions about unstructured data, structured data, live data, and video summary.
+
 [examples](./examples/): Contains examples script for finetuning and inference of the Llama 2 model as well as how to use them safely.
 
 [inference](src/llama_recipes/inference/): Includes modules for inference for the fine-tuned models.