This project is a quantized version of TheDrummer's Cydonia-24B-v4.3 model. It uses llama.cpp for quantization processing, aiming to provide model files of different quantization types to meet the needs of different hardware and performance. It is a large language model with 24B parameters, mainly used for text generation tasks.

Natural Language ProcessingGguf

This is a quantized version of the vanta-research/atom-v1-preview-12b model, offering a variety of quantization types. It is suitable for multiple scenarios such as dialogue, collaboration, and education. This model is based on the Gemma architecture and supports English language processing.

MultimodalTransformersEnglish

Qwen3-32B is the latest generation of large language models in the Qwen series, with powerful reasoning, instruction-following, intelligent agent interaction, and multilingual processing capabilities. It supports over 100 languages and dialects and can seamlessly switch between thinking and non-thinking modes, providing users with a natural and smooth dialogue experience.

Natural Language ProcessingTransformers

kotodama-1.5b-a0.3b-sft is a large language model that undergoes supervised fine-tuning based on noname0202/kotodama-1.5b-a0.3b-pt. This model is trained using the TRL framework and is specifically optimized for text generation tasks, effectively addressing issues related to natural language processing.

Natural Language ProcessingTransformers

Profluent - E1 is a faithful implementation of the E1 model by Profluent Bio, released by Synthyra. It is a pre-trained language model focused on protein sequence processing, integrating Hugging Face AutoModel compatibility and providing efficient embedding capabilities, aiming to simplify protein sequence analysis and representation learning in bioinformatics tasks.

Scientific ComputingTransformers

This is a sentence transformer model fine-tuned based on sentence-transformers/all-mpnet-base-v2, which can map text to a 768-dimensional dense vector space and support various natural language processing tasks such as semantic similarity calculation, semantic search, and text classification.

Natural Language ProcessingSentence-transformers

This model is a fine-tuned version based on meta-llama/Llama-3.3-70B-Instruct. It is trained using the mlabonne/FineTome-100k dataset, which contains 100k token data. The model is fine-tuned using the Unsloth and Huggingface TRL libraries and supports English language processing.

Natural Language ProcessingTransformersEnglish

A text generation model developed based on the MLX library, focusing on natural language processing tasks and providing developers with an efficient text generation solution.

Natural Language ProcessingMlxEnglish

This is a 🤗 Transformers model published on the Hugging Face Hub. Specific information needs to be obtained from the model page. This model is based on the Transformer architecture and is suitable for various natural language processing tasks.

Natural Language ProcessingTransformers

Aquif-3.5-Max-42B-A3B is a large language model with 42 billion parameters, which has undergone MXFP4_MOE quantization processing. It optimizes inference efficiency while maintaining high-quality text generation capabilities. This model is based on an advanced mixture-of-experts architecture and is suitable for various natural language processing tasks.

Natural Language ProcessingGguf

Olmo 3 is a brand - new 32B parameter language model family developed by the Allen Institute for AI (Ai2), which includes variants such as Base, Instruct, and Think. This model is trained on the Dolma 3 dataset, supports long - context processing of up to 65,536 tokens, and aims to promote the development of language model science. The model is fully open - source and follows the Apache 2.0 license.

Natural Language ProcessingTransformersEnglish

This is a statically quantized version of the gravitee-io/very-small-prompt-compression model, specifically designed for prompt compression and text summarization tasks. The model is trained on the Dolly-15k prompt compression dataset and supports English language processing, offering multiple quantization levels to choose from.

Natural Language ProcessingTransformersEnglish

Hebrew_Nemo is a large language model focused on Hebrew processing. It has undergone instruction fine-tuning and supports text generation and dialogue interaction. This version is the GGUF quantized version of the original model, offering multiple quantization levels.

Natural Language ProcessingTransformersMultiple Languages

Kimi Linear is a hybrid linear attention architecture that outperforms traditional full attention methods in various scenarios, including short and long contexts, as well as reinforcement learning extension mechanisms. It can effectively solve the problem of low efficiency of traditional attention mechanisms in long context tasks and bring more efficient solutions to fields such as natural language processing.

Natural Language ProcessingTransformers

Lamapi/next-12b is a large language model based on 12B parameters. It is fine-tuned with a multilingual dataset, supports more than 50 languages, has efficient text generation capabilities, and is suitable for natural language processing tasks in multiple fields such as chemistry, code, biology, finance, and law.

Natural Language ProcessingTransformersMultiple Languages

Lamapi/next-12b is a multilingual large language model with 12 billion parameters, offering multiple quantized versions and supporting various natural language processing tasks such as text generation, question answering, and chatting. This model is trained on multiple domain datasets and features high efficiency and lightweight characteristics.

Natural Language ProcessingTransformersMultiple Languages

A quantized version of LightOnOCR-1B-1025, specifically designed for image-to-text tasks and widely used in fields such as document understanding and visual language processing. This model supports multiple European languages and is suitable for scenarios such as OCR, PDF processing, and table recognition.

MultimodalGgufMultiple Languages

i3-80M is an innovative hybrid architecture language model that combines the advantages of convolutional/recurrent layers and full attention layers. The model adopts RWKV-style time mixing and Mamba state space dynamics to achieve efficient sequence processing in the early layers and uses the standard multi-head attention mechanism in the deep layers for complex pattern recognition.

Natural Language ProcessingTransformersEnglish

Llama-4-Maverick-17B-128E-Instruct-NVFP4 is a multilingual large language model that has undergone FP4 quantization processing. It is based on the Meta-Llama-3.1 architecture and is specifically designed for business and research purposes. By quantizing the weights and activations to the FP4 data type, this model significantly reduces the disk space and GPU memory requirements while maintaining good performance.

Natural Language ProcessingSafetensorsMultiple Languages

This is a multimodal model that supports multilingual processing, covering multiple fields such as natural language processing, code processing, and audio processing. It can perform various tasks such as automatic speech recognition, speech summarization, speech translation, and visual question answering.

MultimodalSafetensorsMultiple Languages