Machine-Learning-Guide VS transformers

Compare Machine-Learning-Guide vs transformers and see what are their differences.

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Machine-Learning-Guide transformers
6 176
437 125,369
- 1.7%
6.2 10.0
4 months ago 1 day ago
Python Python
- Apache License 2.0
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.

Machine-Learning-Guide

Posts with mentions or reviews of Machine-Learning-Guide. We have used some of these posts to build our list of alternatives and similar projects.

transformers

Posts with mentions or reviews of transformers. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-05-01.

What are some alternatives?

When comparing Machine-Learning-Guide and transformers you can also consider the following projects:

Text2Poster-ICASSP-22 - Official implementation of the ICASSP-2022 paper "Text2Poster: Laying Out Stylized Texts on Retrieved Images"

fairseq - Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

pytorch-forecasting - Time series forecasting with PyTorch

sentence-transformers - Multilingual Sentence & Image Embeddings with BERT

pinferencia - Python + Inference - Model Deployment library in Python. Simplest model inference server ever.

llama - Inference code for Llama models

prtm - Deep learning for protein science

transformer-pytorch - Transformer: PyTorch Implementation of "Attention Is All You Need"

igel - a delightful machine learning tool that allows you to train, test, and use models without writing code

text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.

thinc - 🔮 A refreshing functional take on deep learning, compatible with your favorite libraries

huggingface_hub - The official Python client for the Huggingface Hub.