Showing 2 open source projects for "transformers"

View related business solutions
  • Custom VMs From 1 to 96 vCPUs With 99.95% Uptime Icon
    Custom VMs From 1 to 96 vCPUs With 99.95% Uptime

    General-purpose, compute-optimized, or GPU/TPU-accelerated. Built to your exact specs.

    Live migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
    Start Free
  • Train ML Models With SQL You Already Know Icon
    Train ML Models With SQL You Already Know

    BigQuery automates data prep, analysis, and predictions with built-in AI assistance.

    Build and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
    Start Free
  • 1
    Transformers

    Transformers

    State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX

    Hugging Face Transformers provides APIs and tools to easily download and train state-of-the-art pre-trained models. Using pre-trained models can reduce your compute costs, carbon footprint, and save you the time and resources required to train a model from scratch. These models support common tasks in different modalities. Text, for tasks like text classification, information extraction, question answering, summarization, translation, text generation, in over 100 languages.
    Downloads: 4 This Week
    Last Update:
    See Project
  • 2
    DETR

    DETR

    End-to-end object detection with transformers

    PyTorch training code and pretrained models for DETR (DEtection TRansformer). We replace the full complex hand-crafted object detection pipeline with a Transformer, and match Faster R-CNN with a ResNet-50, obtaining 42 AP on COCO using half the computation power (FLOPs) and the same number of parameters. Inference in 50 lines of PyTorch. What it is. Unlike traditional computer vision techniques, DETR approaches object detection as a direct set prediction problem. It consists of a set-based...
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next