wangcongcong123/ttt
A package for fine-tuning Transformers with TPUs, written in Tensorflow2.0+
This project helps machine learning engineers efficiently train large language models, specifically Transformer models, for various natural language processing tasks. It takes raw text data or pre-tokenized inputs and fine-tunes models like BERT or T5 to produce specialized models for tasks such as text classification, translation, or summarization. It's designed for users who work with large datasets and require powerful computational resources like TPUs or GPUs to accelerate model training.
No commits in the last 6 months.
Use this if you are a machine learning engineer or researcher needing to fine-tune Transformer-based models on large datasets using Google's TPUs or powerful GPUs.
Not ideal if you are looking for a simple, low-code solution for NLP tasks or if your work does not involve training custom deep learning models.
Stars
37
Forks
5
Language
Python
License
MIT
Category
Last pushed
Mar 10, 2021
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/transformers/wangcongcong123/ttt"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
huggingface/tokenizers
💥 Fast State-of-the-Art Tokenizers optimized for Research and Production
megagonlabs/ginza-transformers
Use custom tokenizers in spacy-transformers
Kaleidophon/token2index
A lightweight but powerful library to build token indices for NLP tasks, compatible with major...
Hugging-Face-Supporter/tftokenizers
Use Huggingface Transformer and Tokenizers as Tensorflow Reusable SavedModels
NVIDIA/Cosmos-Tokenizer
A suite of image and video neural tokenizers