Add Stable Beluga 2 to readme (#424)

README.md

@@ -8,15 +8,15 @@
     <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:
+Generate text with distributed [LLaMA 2 (70B)](https://huggingface.co/meta-llama/Llama-2-70b-hf), [Stable Beluga 2](https://huggingface.co/stabilityai/StableBeluga2), [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:
 
 ```python
 from transformers import AutoTokenizer
 from petals import AutoDistributedModelForCausalLM
 
-model_name = "enoch/llama-65b-hf"
+model_name = "stabilityai/StableBeluga2"
 # You can also use "meta-llama/Llama-2-70b-hf", "meta-llama/Llama-2-70b-chat-hf",
-# "bigscience/bloom", or "bigscience/bloomz"
+# repos with LLaMA-65B, "bigscience/bloom", or "bigscience/bloomz"
 
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 model = AutoDistributedModelForCausalLM.from_pretrained(model_name)
@@ -33,7 +33,7 @@ print(tokenizer.decode(outputs[0]))  # A cat sat on a mat...
 
 🦙 **Want to run 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), then run `huggingface-cli login` in the terminal before loading the model. Or just try it in our [chatbot app](https://chat.petals.dev).
 
-📋 **Terms of use.** Make sure you follow the model license (see the ones for [LLaMA 2](https://bit.ly/llama2-license), [LLaMA](https://bit.ly/llama-license) and [BLOOM](https://bit.ly/bloom-license)).
+📋 **Terms of use.** Make sure you follow the model license (see [LLaMA 2](https://bit.ly/llama2-license), [Stable Beluga 2](https://huggingface.co/stabilityai/StableBeluga2/blob/main/LICENSE.txt), [LLaMA](https://bit.ly/llama-license), and [BLOOM](https://bit.ly/bloom-license)).
 
 🔏 **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.
 
@@ -48,7 +48,7 @@ Petals is a community-run system &mdash; we rely on people sharing their GPUs. Y
 ```bash
 conda install pytorch pytorch-cuda=11.7 -c pytorch -c nvidia
 pip install git+https://github.com/bigscience-workshop/petals
-python -m petals.cli.run_server enoch/llama-65b-hf --adapters timdettmers/guanaco-65b
+python -m petals.cli.run_server stabilityai/StableBeluga2 --torch_dtype float16
 ```
 
 🪟 **Windows + WSL.** Follow the guide on our [Wiki](https://github.com/bigscience-workshop/petals/wiki/Run-Petals-server-on-Windows).
@@ -57,12 +57,10 @@ python -m petals.cli.run_server enoch/llama-65b-hf --adapters timdettmers/guanac
 
 ```bash
 sudo docker run -p 31330:31330 --ipc host --gpus all --volume petals-cache:/cache --rm learningathome/petals:main \
-    python -m petals.cli.run_server --port 31330 enoch/llama-65b-hf --adapters timdettmers/guanaco-65b
+    python -m petals.cli.run_server --port 31330 stabilityai/StableBeluga2 --torch_dtype float16
 ```
 
-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)!
+These commands will host a part of [Stable Beluga 2](https://huggingface.co/stabilityai/StableBeluga2) on your machine. You can also host `meta-llama/Llama-2-70b-hf`, `meta-llama/Llama-2-70b-chat-hf`, repos with LLaMA-65B, `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.
 
 🦙 **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`:
 
@@ -70,6 +68,8 @@ These commands host a part of LLaMA-65B with optional [Guanaco](https://huggingf
 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, 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`.