rbitr/ferrite
Simple, lightweight transformers in Fortran
This tool helps non-developers generate numerical representations, called embeddings, from text using a pre-trained Sentence Transformer model. You input text, and it outputs a sequence of numbers that capture the meaning of the text. This is useful for scientists, marketers, or anyone who needs to perform semantic search or text comparison tasks without deep machine learning expertise.
No commits in the last 6 months.
Use this if you need to quickly and transparently convert text into numerical embeddings for tasks like semantic search or measuring text similarity, especially on systems where traditional ML frameworks might be overly complex or resource-intensive for inference.
Not ideal if you need to train new transformer models, require support for a wide variety of transformer architectures beyond DistilBert, or prefer a high-level, abstract interface for complex natural language processing tasks.
Stars
17
Forks
1
Language
Fortran
License
MIT
Category
Last pushed
Nov 17, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/embeddings/rbitr/ferrite"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
MinishLab/model2vec
Fast State-of-the-Art Static Embeddings
AnswerDotAI/ModernBERT
Bringing BERT into modernity via both architecture changes and scaling
tensorflow/hub
A library for transfer learning by reusing parts of TensorFlow models.
Embedding/Chinese-Word-Vectors
100+ Chinese Word Vectors 上百种预训练中文词向量
twang2218/vocab-coverage
语言模型中文认知能力分析