Results for bpe

Javascript BPE Encoder Decoder for GPT-2 / GPT-3

tiktoken is a fast [BPE](https://en.wikipedia.org/wiki/Byte_pair_encoding) tokeniser for use with OpenAI's models.

A pure JavaScript implementation of a BPE tokenizer (Encoder/Decoder) for GPT-2 / GPT-3 / GPT-4 and other OpenAI models

Javascript BPE Encoder Decoder for GPT-2 / GPT-3

Fast tokenizer for language models, supporting BPE, Unigram and WordPiece tokenization

Offline BPE tokenizer for OpenAI, Anthropic, and Gemini — zero dependencies

Core runtime for counting BPE tokens.

BPE tokenizer used for the NovelAI frontend.

MCP server for the BPE (Bitcoin Pricing Engine) market-data API. Lets Claude Desktop, Cursor, and other MCP-enabled agents query consolidated BTC pricing, ML signals, funding-rate skew, and natural-language market briefings.

Javascript BPE Encoder Decoder for GPT-2 / GPT-3

Build your own vocabulary from application-specific corpus using Byte pair encoding (BPE) algorithm.

Javascript BPE Encoder Decoder for GPT-2 / GPT-3. The "gpt-3-encoder" module provides functions for encoding and decoding text using the Byte Pair Encoding (BPE) algorithm. It can be used to process text data for input into machine learning models, or to

WebAssembly bindings for bpe-openai tokenizer

CLI tool to visualize Byte Pair Encoding (BPE) merge steps

BPE tokenizer data files for LLMs (o200k_base, cl100k_base, DeepSeek V3/V2)

A simple JavaScript implementation of Byte Pair Encoding (BPE)

BPE Frontend Code.

WASM bindings for the tiktoken BPE tokenizer

Estimate and count tokens (incl. exact OpenAI BPE) and input costs for LLM API calls

Javascript BPE Encoder Decoder for GPT-2 / GPT-3. The "gpt-3-encoder" module provides functions for encoding and decoding text using the Byte Pair Encoding (BPE) algorithm. It can be used to process text data for input into machine learning models, or to

Javascript BPE Encoder Decoder for GPT-2 / GPT-3

n8n node for working with BPE Tokens with OpenAI's GPT models in mind.

Javascript BPE Encoder Decoder for GPT-2 / GPT-3

TypeScript + Rust Native machine learning library. Matrix ops, layers (Dense, Embedding, RNN, LSTM, GRU, MultiHeadAttention, etc), models (Sequential, Transformers), dan BPE tokenizer.