lm-human-preferences VS community-events

Compare lm-human-preferences vs community-events and see what are their differences.

lm-human-preferences

Code for the paper Fine-Tuning Language Models from Human Preferences (by openai)

community-events

Place where folks can contribute to 🤗 community events (by huggingface)
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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 -
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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

Posts with mentions or reviews of lm-human-preferences. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-02-14.

community-events

Posts with mentions or reviews of community-events. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-02-17.

What are some alternatives?

When comparing lm-human-preferences and community-events you can also consider the following projects:

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"