Link FAQ in readme (#260)

README.md

@@ -35,7 +35,7 @@ for input_ids, labels in data_loader:
 
 ### Connect your GPU and increase Petals capacity
 
-Run this in an [Anaconda](https://www.anaconda.com) env:
+Run this in an [Anaconda](https://www.anaconda.com) env (requires Linux and Python 3.7+):
 
 ```bash
 conda install pytorch pytorch-cuda=11.7 -c pytorch -c nvidia
@@ -43,16 +43,18 @@ pip install -U petals
 python -m petals.cli.run_server bigscience/bloom-petals
 ```
 
-Or use our [Docker](https://www.docker.com) image:
+Or use our [Docker](https://www.docker.com) image (works on Linux, macOS, and Windows with [WSL2](https://learn.microsoft.com/en-us/windows/ai/directml/gpu-cuda-in-wsl)):
 
 ```bash
-sudo docker run --net host --ipc host --gpus all --volume petals-cache:/cache --rm \
-    learningathome/petals:main python -m petals.cli.run_server bigscience/bloom-petals
+sudo docker run -p 31330:31330 --ipc host --gpus all --volume petals-cache:/cache --rm \
+    learningathome/petals:main python -m petals.cli.run_server bigscience/bloom-petals --port 31330
 ```
 
+📚 See [FAQ](https://github.com/bigscience-workshop/petals/wiki/FAQ:-Frequently-asked-questions#running-a-server) to learn how to configure the server to use multiple GPUs, address common issues, etc.
+
 You can also host [BLOOMZ](https://huggingface.co/bigscience/bloomz), a version of BLOOM fine-tuned to follow human instructions in the zero-shot regime — just replace `bloom-petals` with `bloomz-petals`.
 
-🔒 This does not allow others to run custom code on your computer. Learn more about security [here](https://github.com/bigscience-workshop/petals/wiki/Security,-privacy,-and-AI-safety).
+🔒 Hosting a server does not allow others to run custom code on your computer. Learn more about security [here](https://github.com/bigscience-workshop/petals/wiki/Security,-privacy,-and-AI-safety).
 
 💬 If you have any issues or feedback, let us know on [our Discord server](https://discord.gg/D9MwApKgWa)!
 
@@ -64,16 +66,18 @@ Basic tutorials:
 - Prompt-tune BLOOM to create a personified chatbot: [tutorial](https://colab.research.google.com/github/bigscience-workshop/petals/blob/main/examples/prompt-tuning-personachat.ipynb)
 - Prompt-tune BLOOM for text semantic classification: [tutorial](https://colab.research.google.com/github/bigscience-workshop/petals/blob/main/examples/prompt-tuning-sst2.ipynb)
 
-Example apps built with Petals:
-
-- [Chatbot web app](http://chat.petals.ml) (connects to Petals via an HTTP endpoint): [source code](https://github.com/borzunov/chat.petals.ml)
-
 Useful tools and advanced guides:
 
+- [Chatbot web app](http://chat.petals.ml) (connects to Petals via an HTTP endpoint): [source code](https://github.com/borzunov/chat.petals.ml)
 - [Monitor](http://health.petals.ml) for the public swarm: [source code](https://github.com/borzunov/health.petals.ml)
 - Launch your own swarm: [guide](https://github.com/bigscience-workshop/petals/wiki/Launch-your-own-swarm)
 - Run a custom foundation model: [guide](https://github.com/bigscience-workshop/petals/wiki/Run-a-custom-model-with-Petals)
 
+Learning more:
+
+- Frequently asked questions: [FAQ](https://github.com/bigscience-workshop/petals/wiki/FAQ:-Frequently-asked-questions)
+- In-depth system description: [paper](https://arxiv.org/abs/2209.01188)
+
 📋 If you build an app running BLOOM with Petals, make sure it follows the BLOOM's [terms of use](https://huggingface.co/bigscience/bloom).
 
 ## How does it work?
@@ -87,23 +91,11 @@ Useful tools and advanced guides:
 </p>
 
 <p align="center">
+    📚 &nbsp;<b><a href="https://github.com/bigscience-workshop/petals/wiki/FAQ:-Frequently-asked-questions">See FAQ</a></b>
+    &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
     📜 &nbsp;<b><a href="https://arxiv.org/pdf/2209.01188.pdf">Read paper</a></b>
 </p>
 
-## FAQ
-
-1. **What's the motivation for people to host model layers in the public swarm?**
-
-    People who run inference and fine-tuning themselves get a certain speedup if they host a part of the model locally. Some may be also motivated to "give back" to the community helping them to run the model (similarly to how [BitTorrent](https://en.wikipedia.org/wiki/BitTorrent) users help others by sharing data they have already downloaded).
-
-    Since it may be not enough for everyone, we are also working on introducing explicit __incentives__ ("bloom points") for people donating their GPU time to the public swarm. Once this system is ready, people who earned these points will be able to spend them on inference/fine-tuning with higher priority or increased security guarantees, or (maybe) exchange them for other rewards.
-
-2. **Why is the platform named "Petals"?**
-
-    "Petals" is a metaphor for people serving different parts of the model. Together, they host the entire language model &mdash; [BLOOM](https://huggingface.co/bigscience/bloom).
-
-    While our platform focuses on BLOOM now, we aim to support more [foundation models](https://arxiv.org/abs/2108.07258) in future.
-
 ## Installation
 
 Here's how to install Petals with conda: