lm-human-preferences
community-events
Our great sponsors
lm-human-preferences | community-events | |
---|---|---|
8 | 8 | |
1,106 | 377 | |
5.3% | 4.2% | |
2.7 | 7.2 | |
9 months ago | 5 months ago | |
Python | Jupyter Notebook | |
MIT License | - |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
lm-human-preferences
- Ask HN: Open-source GPT-3 alternatives
- El éxito continuo de OpenAI: Y como llegaron a crear la IA más avanzada del 2023. ChatGPT.
-
Sam Altman on the best and worst case scenario for AI - "...the good case is just so unbelievably good that you sound like a really crazy person to start talking about it."
Lest you think that that sounds like a too galaxy-brained possibility, it has already happened at OpenAI (scroll down to "Bugs can optimize for bad behavior"), just with a model that was very far from being capable enough to be dangerous.
-
Value head in GPT2
Found relevant code at https://github.com/openai/lm-human-preferences + all code implementations here
-
Should we stick to the devil we know?
That's why, when they're serious, they use RL for finetuning from human preferences (would be hilarious if this attempt to solve the terrible bias you take to be evidence of AGI threat ends up creating a Woke Singleton itself, btw); it's a powerful general approach, and I see no sign of it being applied here.
-
Dall-E 2
The kind of measures they are taking, like simply deleting wholesale anything problematic, don't really have a '-1'.
But amusingly, exactly that did happen in one of their GPT experiments! https://openai.com/blog/fine-tuning-gpt-2/
- Discussion Thread
-
[D] Applications for using reinforcement learning to fine-tune GPT-2
Code for https://arxiv.org/abs/1909.08593 found: https://github.com/openai/lm-human-preferences
community-events
-
Controlling Stable Diffusion with JAX & Diffusers using TPU v4
Best applications that will come out of this sprint will receive prizes. You can find more information here. If you want to get started, simply join huggingface.co/discord, take the role 🧨 Diffusers and head to #jax-diffusers-ideas to share your idea or join one of the teams, and fill this form: https://forms.gle/t3M7aNPuLL9V1sfa9
-
JAX & Diffusers to Control Stable Diffusion (with TPUs ⚡️ )
It will start on 17th of April. To join us, you can join huggingface.co/join/discord and take the role Diffusers from #role-assignment. After this, simply fill the form provided in this guide to later get access to TPUs. https://github.com/huggingface/community-events/tree/main/jax-controlnet-sprint
- “Control Stable Diffusion” Sprint kicks off with free TPU-v4 from Google
-
Free compute to train custom ControlNet by Hugging Face
Details and sign-up: https://github.com/huggingface/community-events/tree/main/jax-controlnet-sprint
-
How can I create a dataset to refine Whisper AI from old videos with subtitles?
For the training, I extremely recommend checking out the Whisper Fine-Tuning Event. It has a python script to train in one command, tons of tips, even a walkthrough video.
- I am using OpenAi's whisper transcription/translation model. I am wondering if I can improve it's performance by optimizing the audio files somehow. What features of audio files should I look into to make the whisper model perform better?
-
[N] Gradio Blocks + Hugging Face event is starting this week. A hackathon type event from May 17th to May 31st with prizes in which we will create interactive web demos for state-of-the-art machine learning models
We are happy to invite you to the Gradio Blocks Party - a community event in which we will create interactive demos for state-of-the-art machine learning models. Demos are powerful because they allow anyone — not just ML engineers — to try out models in the browser, give feedback on predictions, identify trustworthy models. The event will take place from May 17th to 31st. We will be organizing this event on Github and the Hugging Face discord channel. Prizes will be given at the end of the event, see the Prizes section
-
Dall-E 2
If you're interested in generative models, Hugging Face is putting on an event around generative models right now called the HugGAN sprint, where they're giving away free access to compute to train models like this.
You can join it by following the steps in the guide here: https://github.com/huggingface/community-events/tree/main/hu...
There will also be talks from awesome folks at EleutherAI, Google, and Deepmind
What are some alternatives?
trl - Train transformer language models with reinforcement learning.
dalle-2-preview
GLM-130B - GLM-130B: An Open Bilingual Pre-Trained Model (ICLR 2023)
dalle-mini - DALL·E Mini - Generate images from a text prompt
bevy_retro - Plugin pack for making 2D games with Bevy
tensorrtx - Implementation of popular deep learning networks with TensorRT network definition API
gpt-3 - GPT-3: Language Models are Few-Shot Learners
glide-text2im - GLIDE: a diffusion-based text-conditional image synthesis model
gpt-2 - Code for the paper "Language Models are Unsupervised Multitask Learners"