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Update docs for current project status. (#3730)
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This PR updates the FAQ, which is currently very out of date, to the
current status of the project. It also adds a notice to the introduction
page in the docs that the project has concluded. Feel free to make any
changes if it isn't worded how you would like.
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186 changes: 29 additions & 157 deletions docs/docs/faq.md
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Expand Up @@ -15,12 +15,12 @@ In this page, there are some of the most frequently asked questions.

</summary>

We have released candidate supervised finetuning (SFT) models using both Pythia
and LLaMa, as well as candidate reward models for reinforcement learning from
human feedback training using Pythia, which you can try, and are beginning the
process of applying (RLHF). We have also released the first version of the
OpenAssistant Conversations dataset
[here](https://huggingface.co/datasets/OpenAssistant/oasst1).
This project has concluded. We have released supervised finetuning (SFT) models
using Llama 2, LLaMa, Falcon, Pythia, and StabeLM as well as reinforcement
learning from human feedback trained models and reward models, all of which are
available at [here](https://huggingface.co/OpenAssistant). In addition to our
models, we have released three datasets from OpenAssistant conversations, and a
[research paper](https://arxiv.org/abs/2304.07327).

</details>

Expand All @@ -31,9 +31,8 @@ OpenAssistant Conversations dataset

</summary>

You can play with our best candidate model
[here](https://open-assistant.io/chat) and provide thumbs up/down responses to
help us improve the model in future!
Our online demonstration is no longer available, but the models remain available
to download [here](https://huggingface.co/OpenAssistant).

</details>

Expand All @@ -44,37 +43,18 @@ help us improve the model in future!

</summary>

The candidate Pythia SFT models are
All of our models are
[available on HuggingFace](https://huggingface.co/OpenAssistant) and can be
loaded via the HuggingFace Transformers library. As such you may be able to use
them with sufficient hardware. There are also spaces on HF which can be used to
chat with the OA candidate without your own hardware. However, these models are
not final and can produce poor or undesirable outputs.
loaded via the HuggingFace Transformers library or other runners if converted.
As such you may be able to use them with sufficient hardware. There are also
spaces on HF which can be used to chat with the OA candidate without your own
hardware. However, some of these models are not final and can produce poor or
undesirable outputs.

LLaMa SFT models cannot be released directly due to Meta's license but XOR
LLaMa (v1) SFT models cannot be released directly due to Meta's license but XOR
weights are released on the HuggingFace org. Follow the process in the README
there to obtain a full model from these XOR weights.

</details>

<details>
<summary>

### Is there an API available?

</summary>

There is no API currently available for Open Assistant. Any mention of an API in
documentation is referencing the website's internal API. We understand that an
API is a highly requested feature, but unfortunately, we can't provide one at
this time due to a couple of reasons. Firstly, the inference system is already
under high load and running off of compute from our sponsors. Secondly, the
project's primary goal is currently data collection and model training, not
providing a product.

However, if you're looking to run inference, you can host the model yourself
either on your own hardware or with a cloud provider. We appreciate your
understanding and patience as we continue to develop this project.
there to obtain a full model from these XOR weights. Llama 2 models are not
required to be XORed.

</details>

Expand Down Expand Up @@ -102,15 +82,13 @@ inference setup and UI locally unless you wish to assist in development.
All Open Assistant code is licensed under Apache 2.0. This means it is available
for a wide range of uses including commercial use.

The Open Assistant Pythia based models are released as full weights and will be
licensed under the Apache 2.0 license.

The Open Assistant LLaMa based models will be released only as delta weights
meaning you will need the original LLaMa weights to use them, and the license
restrictions will therefore be those placed on the LLaMa weights.
Open Assistant models are released under the license of their respective base
models, be that Llama 2, Falcon, Pythia, or StableLM. LLaMa (not 2) models are
only released as XOR weights, meaning you will need the original LLaMa weights
to use them.

The Open Assistant data is released under a Creative Commons license allowing a
wide range of uses including commercial use.
The Open Assistant data is released under Apache-2.0 allowing a wide range of
uses including commercial use.

</details>

Expand Down Expand Up @@ -138,9 +116,8 @@ you to everyone who has taken part!

</summary>

The model code, weights, and data are free. We are additionally hosting a free
public instance of our best current model for as long as we can thanks to
compute donation from Stability AI via LAION!
The model code, weights, and data are free. Our free public instance of our best
models is not longer available due to the project's conclusion.

</details>

Expand All @@ -151,10 +128,9 @@ compute donation from Stability AI via LAION!

</summary>

The current smallest (Pythia) model is 12B parameters and is challenging to run
on consumer hardware, but can run on a single professional GPU. In future there
may be smaller models and we hope to make progress on methods like integer
quantisation which can help run the model on smaller hardware.
The current smallest models are 7B parameters and are challenging to run on
consumer hardware, but can run on a single professional GPU or be quantized to
run on more widely available hardware.

</details>

Expand All @@ -165,13 +141,7 @@ quantisation which can help run the model on smaller hardware.

</summary>

If you want to help in the data collection for training the model, go to the
website [https://open-assistant.io/](https://open-assistant.io/).

If you want to contribute code, take a look at the
[tasks in GitHub](https://github.com/orgs/LAION-AI/projects/3) and comment on an
issue stating your wish to be assigned. You can also take a look at this
[contributing guide](https://github.com/LAION-AI/Open-Assistant/blob/main/CONTRIBUTING.md).
This project has now concluded.

</details>

Expand All @@ -190,104 +160,6 @@ well as accelerate, DeepSpeed, bitsandbytes, NLTK, and other libraries.

</details>

## Questions about the data collection website

<details>
<summary>

### Can I use ChatGPT to help in training Open Assistant, for instance, by generating answers?

</summary>

No, it is against their terms of service to use it to help train other models.
See
[this issue](https://github.com/LAION-AI/Open-Assistant/issues/471#issuecomment-1374392299).
ChatGPT-like answers will be removed.

</details>

<details>
<summary>

### What should I do if I don't know how to complete the task as an assistant?

</summary>
Skip it.
</details>

<details>
<summary>

### Should I fact check the answers by the assistant?

</summary>

Yes, you should try. If you are not sure, skip the task.

</details>

<details>
<summary>

### How can I see my score?

</summary>

In your [account settings](https://open-assistant.io/account).

</details>

<details>
<summary>

### Can we see how many data points have been collected?

</summary>

You can see a regularly updated interface at
[https://open-assistant.io/stats](https://open-assistant.io/stats).

</details>

<details>
<summary>

### How do I write and label prompts?

</summary>

Check the
[guidelines](https://projects.laion.ai/Open-Assistant/docs/guides/guidelines).

</details>

<details>
<summary>

### Where can I report a bug or create a new feature request?

</summary>

In the [GitHub issues](https://github.com/LAION-AI/Open-Assistant/issues).

</details>

<details>
<summary>

### Why am I not allowed to write about this topic, even though it isn't illegal?

</summary>

We want to ensure that the Open Assistant dataset is as accessible as possible.
As such, it's necessary to avoid any harmful or offensive content that could be
grounds for removal on sites such as Hugging Face. Likewise, we want the model
to be trained to reject as few questions as possible, so it's important to not
include prompts that leave the assistant with no other choice but to refuse in
order to avoid the generation of harmful content.

</details>

## Questions about the development process

<details>
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# Notice

**Open Assistant has now concluded.** Please see
[this video](https://www.youtube.com/watch?v=gqtmUHhaplo) for more information.
Thanks you to all those who made this project possible.

# Introduction

> The FAQ page is available at
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