diff --git a/README.md b/README.md
index ecfb615..0c44ff6 100644
--- a/README.md
+++ b/README.md
@@ -1,8 +1,11 @@
 <p align="center">
     <img src="https://i.imgur.com/7eR7Pan.png" width="400"><br>
     Run large language models at home, BitTorrent-style.<br>
-    Fine-tuning and inference <a href="https://github.com/bigscience-workshop/petals#benchmarks">up to 10x faster</a> than offloading<br><br>
-    <a href="https://pypi.org/project/petals/"><img src="https://img.shields.io/pypi/v/petals.svg?color=green"></a><br>
+    Fine-tuning and inference <a href="https://github.com/bigscience-workshop/petals#benchmarks">up to 10x faster</a> than offloading
+    <br><br>
+    <a href="https://pypi.org/project/petals/"><img src="https://img.shields.io/pypi/v/petals.svg?color=green"></a>
+    <a href="https://discord.gg/tfHfe8B34k"><img src="https://img.shields.io/discord/865254854262652969?label=discord&logo=discord&logoColor=white"></a>
+    <br>
 </p>
 
 Generate text with distributed [LLaMA 2](https://ai.meta.com/llama/) ([70B](https://huggingface.co/meta-llama/Llama-2-70b-hf), [70B-Chat](https://huggingface.co/meta-llama/Llama-2-70b-chat-hf)), [LLaMA-65B](https://github.com/facebookresearch/llama/blob/llama_v1/MODEL_CARD.md), [Guanaco-65B](https://huggingface.co/timdettmers/guanaco-65b) or [BLOOM-176B](https://huggingface.co/bigscience/bloom) and fine‑tune them for your own tasks &mdash; right from your desktop computer or Google Colab:
@@ -34,6 +37,8 @@ print(tokenizer.decode(outputs[0]))  # A cat sat on a mat...
 
 🔏 **Privacy.** Your data will be processed by other people in the public swarm. Learn more about privacy [here](https://github.com/bigscience-workshop/petals/wiki/Security,-privacy,-and-AI-safety). For sensitive data, you can set up a [private swarm](https://github.com/bigscience-workshop/petals/wiki/Launch-your-own-swarm) among people you trust.
 
+💬 **Any questions?** Ping us in [our Discord](https://discord.gg/J29mCBNBvm)!
+
 ### Connect your GPU and increase Petals capacity
 
 Petals is a community-run system &mdash; we rely on people sharing their GPUs. You can check out available servers on our [swarm monitor](https://health.petals.dev) and connect your GPU to help serving one of the models!
@@ -57,14 +62,14 @@ sudo docker run -p 31330:31330 --ipc host --gpus all --volume petals-cache:/cach
 
 These commands host a part of LLaMA-65B with optional [Guanaco](https://huggingface.co/timdettmers/guanaco-65b) adapters on your machine. You can also host `meta-llama/Llama-2-70b-hf`, `meta-llama/Llama-2-70b-chat-hf`, `bigscience/bloom`, `bigscience/bloomz`, and other compatible models from 🤗 [Model Hub](https://huggingface.co/models), or [add support](https://github.com/bigscience-workshop/petals/wiki/Run-a-custom-model-with-Petals) for new model architectures.
 
+💬 **FAQ.** Check out our [Wiki](https://github.com/bigscience-workshop/petals/wiki/FAQ:-Frequently-asked-questions#running-a-server) to learn how to use multple GPUs, restart the server on reboot, etc. If you have any issues, ping us in [our Discord](https://discord.gg/D9MwApKgWa)!
+
 🦙 **Want to host LLaMA 2?** Request access to its weights at the ♾️ [Meta AI website](https://ai.meta.com/resources/models-and-libraries/llama-downloads/) and 🤗 [Model Hub](https://huggingface.co/meta-llama/Llama-2-70b-hf), generate an 🔑 [access token](https://huggingface.co/settings/tokens), then use this command for `petals.cli.run_server`:
 
 ```bash
 python -m petals.cli.run_server meta-llama/Llama-2-70b-chat-hf --token YOUR_TOKEN_HERE
 ```
 
-💬 **FAQ.** Check out our [Wiki](https://github.com/bigscience-workshop/petals/wiki/FAQ:-Frequently-asked-questions#running-a-server) to learn how to use multple GPUs, restart the server on reboot, etc. If you have any issues or feedback, ping us in [our Discord](https://discord.gg/D9MwApKgWa)!
-
 🔒 **Security.** Hosting a server does not allow others to run custom code on your computer. Learn more [here](https://github.com/bigscience-workshop/petals/wiki/Security,-privacy,-and-AI-safety).
 
 🏆 **Thank you!** Once you load and host 10+ blocks, we can show your name or link on the [swarm monitor](https://health.petals.dev) as a way to say thanks. You can specify them with `--public_name YOUR_NAME`.