**Warning: Llama 3.1 support is still under construction!** the latest models require custom RoPE configuration that we do not have in Petals yet; we will update the code to fix that within a day.
Generate text with distributed **Llama (1-3)** (70B), **Falcon** (40B+), **BLOOM** (176B) (or their derivatives), and fine‑tune them for your own tasks — right from your desktop computer or Google Colab:
Generate text with distributed **Llama 3.1** (up to 405B), **Mixtral** (8x7B), **Falcon** (40B+), or **BLOOM** (176B) and fine‑tune them for your own tasks — right from your desktop computer or Google Colab:
```python
from transformers import AutoTokenizer
from petals import AutoDistributedModelForCausalLM
# Choose any model available at https://health.petals.dev
model_name = "petals-team/StableBeluga2" # This one is fine-tuned Llama 2 (70B)
@ -33,22 +31,26 @@ print(tokenizer.decode(outputs[0])) # A cat sat on a mat...
🚀 <b><ahref="https://colab.research.google.com/drive/1uCphNY7gfAUkdDrTx21dZZwCOUDCMPw8?usp=sharing">Try now in Colab</a></b>
</p>
🔏 **Privacy.** Your data will be processed with the help of 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.
🦙 **Want to run Llama?** [Request access](https://huggingface.co/meta-llama/Meta-Llama-3.1-405B-Instruct) to its weights, then run `huggingface-cli login` in the terminal before loading the model. Or just try it in our [chatbot app](https://chat.petals.dev).
🦙 **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).
🔏 **Privacy.** Your data will be processed with the help of 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/KdThf2bWVU)!
## Connect your GPU and increase Petals capacity
Petals is a community-run system — we rely on people sharing their GPUs. You can check out [available models](https://health.petals.dev) and help serving one of them! As an example, here is how to host a part of [Stable Beluga 2](https://huggingface.co/stabilityai/StableBeluga2) on your GPU:
Petals is a community-run system — we rely on people sharing their GPUs. You can help serving one of the [available models](https://health.petals.dev) or host a new model from 🤗 [Model Hub](https://huggingface.co/models)!
As an example, here is how to host a part of [Llama 3.1 (405B) Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-405B-Instruct) on your GPU:
🦙 **Want to host Llama?** [Request access](https://huggingface.co/meta-llama/Meta-Llama-3.1-405B-Instruct) to its weights, then run `huggingface-cli login` in the terminal before loading the model.
🐧 **Linux + Anaconda.** Run these commands for NVIDIA GPUs (or follow [this](https://github.com/bigscience-workshop/petals/wiki/Running-on-AMD-GPU) for AMD):
📚 <b><ahref="https://github.com/bigscience-workshop/petals/wiki/FAQ:-Frequently-asked-questions#running-a-server">Learn more</a></b> (how to use multiple GPUs, start the server on boot, etc.)
</p>
💬 **Any questions?** Ping us in [our Discord](https://discord.gg/X7DgtxgMhc)!
🦙 **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 add `--token YOUR_TOKEN_HERE` to the `python -m petals.cli.run_server` command.
🔒 **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).
💬 **Any questions?** Ping us in [our Discord](https://discord.gg/X7DgtxgMhc)!
🏆 **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`.
## How does it work?
@ -122,22 +122,39 @@ Please see **Section 3.3** of our [paper](https://arxiv.org/pdf/2209.01188.pdf).
Please see our [FAQ](https://github.com/bigscience-workshop/petals/wiki/FAQ:-Frequently-asked-questions#contributing) on contributing.
### 📜 Citation
### 📜 Citations
Alexander Borzunov, Dmitry Baranchuk, Tim Dettmers, Max Ryabinin, Younes Belkada, Artem Chumachenko, Pavel Samygin, and Colin Raffel.
[Petals: Collaborative Inference and Fine-tuning of Large Models.](https://arxiv.org/abs/2209.01188)
_arXiv preprint arXiv:2209.01188,_ 2022.
_Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations)._ 2023.
```bibtex
@article{borzunov2022petals,
@inproceedings{borzunov2023petals,
title = {Petals: Collaborative Inference and Fine-tuning of Large Models},
author = {Borzunov, Alexander and Baranchuk, Dmitry and Dettmers, Tim and Ryabinin, Max and Belkada, Younes and Chumachenko, Artem and Samygin, Pavel and Raffel, Colin},
journal = {arXiv preprint arXiv:2209.01188},
year = {2022},
author = {Borzunov, Alexander and Baranchuk, Dmitry and Dettmers, Tim and Riabinin, Maksim and Belkada, Younes and Chumachenko, Artem and Samygin, Pavel and Raffel, Colin},
booktitle = {Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations)},
pages = {558--568},
year = {2023},
url = {https://arxiv.org/abs/2209.01188}
}
```
Alexander Borzunov, Max Ryabinin, Artem Chumachenko, Dmitry Baranchuk, Tim Dettmers, Younes Belkada, Pavel Samygin, and Colin Raffel.
[Distributed inference and fine-tuning of large language models over the Internet.](https://arxiv.org/abs/2312.08361)
_Advances in Neural Information Processing Systems_ 36 (2024).
```bibtex
@inproceedings{borzunov2023distributed,
title = {Distributed inference and fine-tuning of large language models over the {I}nternet},
author = {Borzunov, Alexander and Ryabinin, Max and Chumachenko, Artem and Baranchuk, Dmitry and Dettmers, Tim and Belkada, Younes and Samygin, Pavel and Raffel, Colin},
booktitle = {Advances in Neural Information Processing Systems},