BRIEF-DETAILS: BioBERT-based NER model fine-tuned for chemical and disease entity recognition, achieving 97% F1-score with excellent chemical detection (98% F1).
BRIEF DETAILS: 7B parameter uncensored GGUF model offering multiple quantization options from 3.1GB to 15.3GB, with recommended Q4_K variants balancing speed and quality.
Brief Details: MERT-v1-330M is a 330M parameter music understanding model trained on 160K hours of audio using MLM paradigm, operating at 24KHz with 75Hz feature rate
Brief-details: Optimized 4-bit quantized version of Qwen2.5-0.5B using Unsloth's Dynamic Quantization, offering 70% memory reduction and 2x faster inference while maintaining accuracy.
Brief Details: State-of-the-art 7B parameter open-source LLM outperforming ChatGPT (March) and Grok-1, with enhanced coding and mathematical capabilities
Brief-details: A DialoGPT-based conversational AI trained to mimic Elon Musk's Twitter communication style, featuring 8 training epochs and ~40% randomness in responses.
Brief-details: A specialized prompt engineering model by embed focused on identifying and mitigating problematic prompt patterns, hosted on HuggingFace.
Brief-details: A similarity calculation model developed by JosephusCheung, created in collaboration with Nyanko Lepsoni and RcINS, designed for computing similarities.
Brief-details: Virtuoso-Small is a 14B parameter LLM optimized for business applications, offering strong instruction-following and reasoning capabilities in a compact form
Brief Details: A 9B parameter multilingual LLM supporting 34 languages, including all EU languages. Built with GQA architecture and trained on 4T tokens.
Brief-details: A fine-tuned version of Helsinki-NLP's English-to-Arabic translation model, optimized on KDE4 dataset with Adam optimizer and linear learning rate scheduling.
Brief-details: CGRE is a state-of-the-art Chinese relation extraction model based on BART, achieving superior performance on datasets like DuIE and HacRED through generative approaches.
Brief-details: Fine-tuned mBART-large-50 model optimized for Persian text summarization, achieving 44.07 ROUGE-1 score with strong BERTScore of 78.95
Brief Details: Transformer-based keyphrase extraction model using KBIR architecture, fine-tuned on OpenKP dataset. Specializes in identifying key phrases from English text documents with high accuracy.
BRIEF-DETAILS: Large-scale Swin Transformer V2 model pre-trained on ImageNet-21k. Features hierarchical architecture, local attention windows, and 192x192 resolution support.
Brief Details: Swin Transformer V2 base model for computer vision, featuring hierarchical feature mapping and improved training stability through residual-post-norm and cosine attention mechanisms.
Brief-details: A 6-layer distilled version of mBERT optimized for Swedish language, achieving comparable F1 scores (0.859) to the original mBERT on SUCX 3.0 dataset.
BRIEF DETAILS: Fine-tuned MT5-base model optimized for Farsi text summarization with ROUGE-1: 33.7, ROUGE-2: 21.28, ROUGE-L: 31.69 scores and BERTScore: 74.52
Brief Details: StyleGAN3-T model fine-tuned for anime face generation, developed by bob80333. Hosted on HuggingFace, specializes in high-quality anime character portraits.
BRIEF DETAILS: TabTransformer: A self-attention based model for structured data learning that combines Transformer architecture with MLP for handling both categorical and numerical features.
Brief-details: RetinaNet object detection model implementing focal loss for balanced detection across scales. Features FPN architecture and COCO2017 dataset training. Optimized for accuracy and speed.
