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  • 1
    Tiktoken

    Tiktoken

    tiktoken is a fast BPE tokeniser for use with OpenAI's models

    tiktoken is a high-performance, tokenizer library (based on byte-pair encoding, BPE) designed for use with OpenAI’s models. It handles encoding and decoding text to token IDs efficiently, with minimal overhead. Because tokenization is a fundamental step in preparing text for models, tiktoken is optimized for speed, memory, and correctness in model contexts (e.g. matching OpenAI’s internal tokenization).
    Downloads: 5 This Week
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  • 2
    autoresearch-mlx

    autoresearch-mlx

    Apple Silicon (MLX) port of Karpathy's autoresearch

    ...It maintains the core autoresearch structure, where an AI agent iteratively edits a training script, executes experiments under a fixed time budget, and evaluates results based on a defined metric such as validation bits per byte. The system is tailored for Apple hardware, leveraging unified memory and MLX capabilities to achieve efficient training on Mac devices. It includes a minimal and focused project structure consisting of data preparation utilities, a modifiable training file, and a program specification that governs the agent’s behavior. The framework logs experiment results and supports continuous iteration, enabling long-running optimization cycles that can reveal hardware-specific performance patterns.
    Downloads: 0 This Week
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  • 3
    minbpe

    minbpe

    Minimal, clean code for the Byte Pair Encoding (BPE) algorithm

    minbpe is a minimal, clean implementation of byte-level Byte Pair Encoding (BPE), the tokenization approach widely used in modern language models. It operates on UTF-8 encoded bytes rather than Unicode characters, which makes it robust to arbitrary text inputs and avoids needing a language-specific character vocabulary. The repository is structured as a teaching-oriented implementation that shows how to train a tokenizer by learning merge rules, then apply those merges to encode text into token IDs and decode tokens back into text. ...
    Downloads: 0 This Week
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  • 4
    LaMDA-pytorch

    LaMDA-pytorch

    Open-source pre-training implementation of Google's LaMDA in PyTorch

    Open-source pre-training implementation of Google's LaMDA research paper in PyTorch. The totally not sentient AI. This repository will cover the 2B parameter implementation of the pre-training architecture as that is likely what most can afford to train. You can review Google's latest blog post from 2022 which details LaMDA here. You can also view their previous blog post from 2021 on the model.
    Downloads: 0 This Week
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