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@@ -1,7 +1,6 @@
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# Llama 2 Fine-tuning / Inference Recipes, Examples and Demo Apps
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-**[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.**
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-
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+**[Update Oct. 31, 2023] We recently released a series of Llama 2 demo apps [here](./demo_apps). These apps show how to run Llama 2 locally, in the cloud, and on-prem, and how to ask Llama 2 questions in general and about custom data (PDF, DB, or live).**
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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).
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@@ -184,16 +183,16 @@ You can read more about our fine-tuning strategies [here](./docs/LLM_finetuning.
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# Demo Apps
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This folder contains a series of Llama2-powered apps:
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* Quickstart Llama deployments and basic interactions with Llama
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- 1. Llama on your Mac and ask Llama general questions
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- 2. Llama on Google Colab
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- 3. Llama on Cloud and ask Llama questions about unstructured data in a PDF
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+1. Llama on your Mac and ask Llama general questions
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+2. Llama on Google Colab
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+3. Llama on Cloud and ask Llama questions about unstructured data in a PDF
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* Specialized Llama use cases:
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- 1. Ask Llama to summarize a video content
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- 2. Ask Llama questions about structured data in a DB
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- 3. Ask Llama questions about live data on the web
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+1. Ask Llama to summarize a video content
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+2. Ask Llama questions about structured data in a DB
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+3. Ask Llama questions about live data on the web
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-**[New] A tutorial on how to deploy [Llama 2 on-prem](./demo_apps/llama-on-prem.md) with vLLM and TGI based API services, as well as client code in Python.**
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+* A tutorial on how to deploy [Llama 2 on-prem](./demo_apps/llama-on-prem.md) with vLLM and TGI based API services, and how to use LangChain to easily query Llama 2 via vLLM and TGI.
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# Repository Organization
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This repository is organized in the following way:
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Jeff Tang