38 results for “topic:pretrained-model”
A Fundamental End-to-End Speech Recognition Toolkit and Open Source SOTA Pretrained Models, Supporting Speech Recognition, Voice Activity Detection, Text Post-processing etc.
Large-scale pretrained models for goal-directed dialog
PyTorch implementation of "FullSubNet: A Full-Band and Sub-Band Fusion Model for Real-Time Single-Channel Speech Enhancement."
Official Pytorch implementation of ReXNet (Rank eXpansion Network) with pretrained models
PyTorch implementation of a collections of scalable Video Transformer Benchmarks.
A PyTorch implementation of the 'FaceNet' paper for training a facial recognition model with Triplet Loss using the glint360k dataset. A pre-trained model using Triplet Loss is available for download.
Real-time hand pose estimation and gesture classification using TensorRT
Image Synthesis + Corgis = <3
PyTorch implementation of "Bootstrap Your Own Latent: A New Approach to Self-Supervised Learning" with DDP and Apex AMP
Mining Discourse Markers for Unsupervised Sentence Representation Learning
Code and released pre-trained model for our ACL 2022 paper: "DialogVED: A Pre-trained Latent Variable Encoder-Decoder Model for Dialog Response Generation"
Custom YOLO11m model for detecting and classifying car body damage (99% shattered glass, 96% flat tire detection accuracy)—optimized for high-capacity inference and assistive use in inspection and service workflows like BMW pre-loaner inspections.
Source code of our SIGIR'24 paper titled "Leave No Patient Behind: Enhancing Medication Recommendation for Rare Disease Patients".
ALBERT trained on Mongolian text corpus
Forest Fire Detection By Convolutional Neural Network
This API utilizes a pre-trained model for emotion recognition from audio files. It accepts audio files as input, processes them using the pre-trained model, and returns the predicted emotion along with the confidence score. The API leverages the FastAPI framework for easy development and deployment.
This is an implementation of electra according to the paper {ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators}
Implemenation of Selective Kernel Networks by pytorch with pretrained weight
Custom YOLOv8 model for detecting and classifying car body damage—optimized for fast inference and assistive use in inspection and service workflows like BMW pre-loaner inspections.
A python library to train Deep Neural Networks on various audio tasks using Self-Supervised backbones.
Lane detection using tensorflow pre-trained model
Glint is a Rust framework designed for creating stateful, graph-based AI systems, enabling efficient multi-step workflows. With features like LLM integration and a graph-based architecture, Glint helps developers build powerful AI solutions with ease. 🐙✨
Blip Image Captioning + GPT-2 Happy Model: Generate joyful responses to image captions using state-of-the-art NLP and computer vision. Pretrained models and data preprocessing included for seamless integration. Explore the intersection of deep learning, sentiment analysis, and language generation
A repository which contains dataset and a pre-trained Snips model for the Automotive Grade Linux's NLU intent engine.
Skin Lesion Classifier- Focusing On Malignant melanoma
Using OpenCV's pretrained model yolov3 for real time object detection. (faster)
Sentiment analysis using bert
🎤 Enable voice recognition for the Doubao input method using Python; ideal for learning and research with a focus on audio processing.
Official implementation of SpottingDiffusion : A CNN-based method of detecting AI generated images.
This is the LLM money saver library for the developers, testers, product guys or startups