awesome-repositories.com
Blog
awesome-repositories.com

Découvrez les meilleurs dépôts open-source grâce à notre recherche par IA.

ExplorerRecherches sélectionnéesAlternatives open sourceLogiciels auto-hébergésBlogPlan du site
ProjetÀ proposNotre méthodologiePresseServeur MCP
Mentions légalesConfidentialitéConditions d'utilisation
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
·

2 dépôts

Awesome GitHub RepositoriesTensor Record Serialization

Specialized binary serialization formats used to stream large tensor datasets from disk.

Distinct from Disk-Serialized Collection Libraries: Existing candidates focus on cache persistence or filesystem formats, not ML-specific record serialization like TFRecords.

Explore 2 awesome GitHub repositories matching data & databases · Tensor Record Serialization. Refine with filters or upvote what's useful.

Awesome Tensor Record Serialization GitHub Repositories

Trouvez les meilleurs dépôts grâce à l'IA.Nous recherchons les dépôts les plus pertinents grâce à l'IA.
  • tensorflow/rustAvatar de tensorflow

    tensorflow/rust

    5,480Voir sur GitHub↗

    This project provides Rust bindings for the TensorFlow C API, serving as a tensor computation interface and machine learning library. It enables the construction and execution of machine learning models and neural networks by bridging a systems language to high-performance backends. The framework supports GPU-accelerated computing to increase the speed of model training and inference by offloading mathematical operations to graphics processing units. It offers both graph-based computation for defining static network architectures and an eager execution mode for immediate operation calls durin

    Uses a specialized binary format to efficiently stream large datasets from disk into memory.

    Rust
    Voir sur GitHub↗5,480
  • kimiyoung/transformer-xlAvatar de kimiyoung

    kimiyoung/transformer-xl

    3,703Voir sur GitHub↗

    This project is an implementation of the Transformer-XL language model, a neural network architecture designed for long-context language modeling. It provides frameworks for training and deploying models that capture long-term dependencies and relationships in text sequences that extend beyond a fixed context window. The implementation supports both PyTorch and TensorFlow, allowing for distributed training across multiple GPUs and host nodes. It employs a recurrent mechanism to maintain coherence in extended sequences, utilizing segment-level recurrence and state-based memory reuse. The code

    Utilizes specialized binary serialization formats to stream large tensor datasets from disk for high-throughput training.

    Python
    Voir sur GitHub↗3,703
  1. Home
  2. Data & Databases
  3. Tensor Record Serialization