BRIEF-DETAILS: Metis is a foundation speech generation model using masked pre-training, supporting TTS, voice conversion, speech enhancement & more with just 20M parameters.
Brief-details: T5-based question-answering model fine-tuned on SQuAD dataset. Optimized with FP16 quantization for efficient inference. Suitable for chatbot and QA applications.
BRIEF-DETAILS: T5-based paraphrase generation model, quantized to FP16 for efficient inference. Achieves 78% ROUGE-1 score, trained on chatgpt-paraphrases dataset.
Brief Details: Video encoder model by OpenGVLab for training VideoChat-Flash, designed for efficient video understanding and processing tasks
BRIEF DETAILS: A 14B parameter merged LLM using SLERP method, combining li-14b-v0.4 and miscii-14b models. Strong performance in IFEval (79.23%) and MATH tasks (53.32%).
Brief-details: GGUF quantized version of Patricide-Magnum-12B with multiple compression options (3.1GB-10.2GB), optimized for efficient deployment with imatrix quantization.
Brief-details: State-of-the-art theorem proving model built on Qwen2.5-Math-7B, achieves 72.95% on MiniF2F test benchmark using BFS approach without critic model.
Brief-details: A 3B parameter distilled LLaMA model optimized for efficient reasoning, featuring specialized chat templates and strong performance on benchmark tasks (23.27 avg score)
Brief-details: A quantized GGUF version of gemma-9B optimized for llama.cpp deployment, offering 9B parameters with Q4_K_M quantization for efficient local inference.
BRIEF-DETAILS: Third-gen ZYH-LLM model with 14B params, achieving 85.78 IFEval score. Uses advanced merging techniques across multiple Qwen2.5 variants.
Brief Details: A specialized LoRA model for black & white sketches, trained on 33 images with unique "333 Pro Sketch" trigger word. Optimized for 1280x832 resolution.
BRIEF DETAILS: Experimental 14B parameter model utilizing novel arcee_fusion merge method, combining Lamarck and Qwenvergence models. Strong in GPQA and reasoning with excellent prose generation capabilities.
BRIEF-DETAILS: 24B parameter creative writing model supporting ChatML/Alpaca formats. Fine-tuned on RP/story data with flexible instruction following and creative generation capabilities.
Brief Details: A detailed comparative analysis of DeepSeek and ChatGPT, focusing on technical architecture, language capabilities, reasoning abilities, and cost-effectiveness. DeepSeek excels in Chinese language processing and offers cost-effective open-source solutions.
Brief Details: A 1B parameter instruction-tuned LLaMA variant focused on benchmarking and evaluation, developed by qingy2024 for research purposes
Brief-details: LLaMA 3.1-based GGUF quantized model offering multiple compression variants (Q2_K to Q8_0), optimized for efficient deployment with sizes ranging from 3.3GB to 16.2GB.
Brief-details: A highly optimized GGUF quantization of Perplexity AI's 70B LLaMA model with multiple compression options from 16GB to 75GB, offering flexible deployment choices.
BRIEF-DETAILS: Vision Transformer-based model for classifying images as AI-generated, deepfake, or real with 97.5% accuracy. Built on Google's ViT architecture.
BRIEF DETAILS: Korean-optimized sentence embedding model based on E5, offering 768-dimensional vectors for semantic text analysis. Strong 0.86 Pearson score on STS tasks.
Brief Details: LSTM-based text segmentation model achieving high accuracy (1.00) with exceptional performance on I-Segmento class (F1=1.00) and strong B-Segmento detection (F1=0.79)
Brief-details: A specialized 3-layer Transformer model designed for state-of-the-art sentence segmentation, part of the Segment Any Text (SAT) framework. Lightweight variant.
