Brief Details: BERT multilingual base model supporting 102 languages, 168M parameters, uncased tokenization, ideal for masked language modeling and sequence tasks.
Brief Details: A fine-tuned XLSR-53 model for Russian speech recognition, achieving 13.3% WER on Common Voice, with 3.6M+ downloads and Apache 2.0 license.
Brief-details: Vision Transformer model with 86.6M params for image classification, pre-trained on ImageNet-21k and fine-tuned on ImageNet-1k. Popular with 3.7M+ downloads.
Brief-details: A powerful multilingual speech model with 300M parameters, supporting 126 languages. Pre-trained on 436K hours of audio data using wav2vec 2.0 architecture.
BRIEF DETAILS: Clinical BERT model trained on MIMIC III healthcare data, combining BioBERT initialization with clinical note training for specialized medical NLP tasks.
Brief-details: A fine-tuned Vision Transformer (ViT) model with 85.8M parameters for NSFW image classification, achieving 98% accuracy using an 80k image dataset.
Brief-details: A transformer-based semantic segmentation model fine-tuned for clothes and human parsing, offering 27.4M parameters with strong accuracy (80% mean) across 18 clothing categories.
Brief-details: A powerful multilingual language detection model supporting 20 languages with 99.6% accuracy, based on XLM-RoBERTa, featuring 278M parameters.
BRIEF DETAILS: Compact 22.7M parameter sentence embedding model optimized for semantic search, trained on 215M question-answer pairs with 384-dimensional output vectors.
BRIEF DETAILS: BERT-based sentence embedding model with 109M parameters. Maps sentences to 768D vectors. Deprecated due to low quality - newer alternatives recommended.
Brief-details: A specialized latent diffusion model for image inpainting, based on Stable Diffusion v1.5. Enables high-quality image editing and completion with text prompts.
Brief-details: CLIP ViT-B/16 model trained on LAION-2B dataset, achieving 70.2% ImageNet accuracy. Specialized in zero-shot image classification and retrieval.
Brief Details: Popular text-to-image model trained on LAION-2B dataset. Features 595k training steps at 512x512 resolution with improved classifier-free guidance sampling.
Brief Details: astroBERT is a 110M-parameter BERT-based language model specialized for astrophysics research, featuring masked language modeling and named entity recognition capabilities.
Brief-details: FastText language identification model by Facebook, capable of detecting 217 languages with efficient word representation learning and quick CPU-based processing
Brief Details: A RoBERTa-based sentiment analysis model trained on 124M tweets (2018-2021), offering 3-class classification with high accuracy and Twitter-specific preprocessing.
Brief-details: Advanced NLP model from Microsoft with 304M parameters, achieving SOTA on NLU tasks. Features disentangled attention and enhanced mask decoder.
Brief Details: A 1.01B parameter GPT-2 variant optimized for efficient text generation, featuring F32 tensor type and custom optimizations for improved performance.
Brief-details: Microsoft's DeBERTa base model featuring disentangled attention mechanism, achieving SOTA results on NLU tasks with 88.8% MNLI-m accuracy.
BRIEF DETAILS: BART-large-CNN: 406M parameter transformer-based summarization model fine-tuned on CNN Daily Mail dataset. Achieves ROUGE-1: 42.95, ROUGE-2: 20.81.
BRIEF DETAILS: A compact BERT variant (L=4, H=512) optimized for efficiency, part of smaller BERT family models, MIT licensed with 5.5M+ downloads
