Find recent high-liked Hugging Face models
Determine GPU requirements for large language models
Display benchmark results
Explore and visualize diverse models
Convert a Stable Diffusion XL checkpoint to Diffusers and open a PR
Compare audio representation models using benchmark results
View and compare language model evaluations
Calculate survival probability based on passenger details
Track, rank and evaluate open LLMs and chatbots
Convert PyTorch models to waifu2x-ios format
View and submit machine learning model evaluations
Open Persian LLM Leaderboard
Measure over-refusal in LLMs using OR-Bench
Model Drops Tracker is a tool designed to help users track and discover recent high-liked Hugging Face models. It simplifies the process of staying updated with the latest models in the machine learning community, focusing on models that have gained significant popularity or traction.
What models are included in Model Drops Tracker?
Model Drops Tracker focuses on models from the Hugging Face Model Hub, particularly those that have received high likes or engagement within the community.
How often is the model list updated?
The list is updated in real-time to reflect the latest models and their popularity rankings.
Can I use Model Drops Tracker for commercial purposes?
Yes, Model Drops Tracker is designed to be used by researchers, developers, and businesses alike, with a focus on open-source accessibility.