GitHub
BERT, Tokenizer, Python, WordPiece, pybind11,C++,Flash,Trie
Listed in categories:
Artificial IntelligenceTechGitHub
Description
FlashTokenizer is a high-performance tokenizer library implemented in C, designed for efficient LLM inference. It offers the fastest tokenization speeds and highest accuracy compared to other tokenizers like Hugging Face's BertTokenizerFast, achieving up to 10 times faster performance. FlashTokenizer is built for ease of use and straightforward installation via pip, making it accessible for developers looking to optimize their NLP workflows.
How to use GitHub?
To use FlashTokenizer, install it via pip with the command 'pip install -U flashtokenizer'. Import the library in your Python code and utilize the provided tokenizer classes to tokenize your text efficiently.
Core features of GitHub:
1️⃣
High-speed tokenization for LLM inference
2️⃣
Implemented in C for optimal performance
3️⃣
Supports parallel processing at the C level
4️⃣
Easy installation via pip
5️⃣
Compatible with Python through pybind11
Why could be used GitHub?
| # | Use case | Status | |
|---|---|---|---|
| # 1 | Tokenizing large datasets for NLP applications | ✅ | |
| # 2 | Enhancing the performance of machine learning models | ✅ | |
| # 3 | Real-time text processing in applications requiring fast inference | ✅ | |
Who developed GitHub?
FlashTokenizer is developed by NLPOptimize, a team focused on creating efficient and optimized tools for natural language processing. Their goal is to enhance the performance of NLP applications through innovative solutions.