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Tags: Embeddings

1.openai / CLIP

CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

deep-learning
machine-learning

Jupyter Notebook MIT35K total4.1K forks

+532 stars

from 34,035 · score 6.28

2.agemagician / ProtTrans

ProtTrans is providing state of the art pretrained language models for proteins. ProtTrans was trained on thousands of GPUs from Summit and hundreds of Google TPUs using Transformers Models.

Jupyter Notebook MIT1.3K total169 forks

+9 stars

from 1,314 · score 2.30

3.BaseModelAI / cleora

Cleora AI is a general-purpose open-source model for efficient, scalable learning of stable and inductive entity embeddings for heterogeneous relational data. Created by Synerise.com team.

ai
graphs
synerise
embeddings
ml
machine-learning
+7 more

Jupyter Notebook Other license546 total58 forks

+7 stars

from 539 · score 2.08

Order: Attention Score

Most net stars gained in the window first. The score only puts this gain on a log scale, so the order is the order of the gain.

How the ranking works

Ranked by stars gained in the window. The score is the natural log of one plus that gain, so a repository's rank is exactly its star gain's rank.

score = log1p(net stars gained in the trailing T complete UTC days)

A repository is ranked only when its Star History covers every day of the window and its latest Observation is not missing.

The longest window is 180 days. Star History from the Repository Host goes back at most 180 days before the first daily record that AwesomeRepos made for the repository. A longer window needs more of these daily records first. A repository younger than the window does not rank in it.

The filters select from the same eligible repositories. A repository matches the topics when it has any of them. Total stars is the count now. Last push and creation on the Repository Host count back from the start of today (UTC). The counts beside the languages, licenses, and topics include all ranked repositories in the window. A Tag holds the repositories that have it. See Tags.

A new repository enters the index when it gains stars faster than the published admission threshold, whatever its size. A repository stays in the index after it enters. Thus an archived repository can still rank.

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