This is the quantized version of TheDrummer's Cydonia - R1 - 24B - v4.1 model. It uses the llama.cpp tool for multi-precision quantization processing and can run efficiently under different hardware conditions, providing users with more options.

Natural Language ProcessingGguf

This is a quantized version of TheDrummer's Behemoth R1 123B v2 model, quantized using llama.cpp and imatrix technology. It can significantly reduce model storage space and computational resource requirements while maintaining good performance, making it suitable for running on different devices.

Natural Language ProcessingGguf

NVIDIA DeepSeek R1 FP4 v2 is a text generation model that performs FP4 quantization based on the DeepSeek R1 model of DeepSeek AI. It adopts an optimized Transformer architecture and can be used for commercial and non-commercial purposes. This model is quantized through the TensorRT Model Optimizer, significantly reducing the disk size and GPU memory requirements compared to the FP8 version.

Natural Language ProcessingSafetensors

NVIDIA DeepSeek-R1-0528-FP4 v2 is a quantized version of the DeepSeek R1 0528 model. It adopts an optimized Transformer architecture and is an autoregressive language model. Through FP4 quantization optimization, it reduces the disk size and GPU memory requirements while maintaining high inference efficiency.

Natural Language ProcessingSafetensors

NVIDIA DeepSeek-R1-0528-FP4 is a quantized version of the DeepSeek R1 0528 model. It uses an optimized Transformer architecture, with weights and activation values quantized to the FP4 data type, significantly reducing disk size and GPU memory requirements. It supports the TensorRT-LLM inference engine for efficient inference.

Natural Language ProcessingSafetensors

A quantized version of the DeepSeek R1 0528 model from DeepSeek AI, an autoregressive language model based on an optimized Transformer architecture, which can be used for commercial and non-commercial purposes.

Natural Language ProcessingSafetensors

DeepSeek-R1-0528 is a minor version upgrade model of the DeepSeek R1 series. It significantly improves the inference depth and ability through increased computing resources and algorithm optimization, and performs excellently in multiple benchmark tests such as mathematics and programming.

Natural Language ProcessingTransformers

DeepSeek-R1-0528-AWQ is the AWQ quantized version of DeepSeek R1 0528. Through quantization technology, the model's operating efficiency is improved, code issues are fixed, and more stable services are provided.

Natural Language ProcessingTransformersMultiple Languages

AWQ-quantized version of DeepSeek R1 0528, supports full-context-length operation on 8x80GB GPUs using vLLM.

Natural Language ProcessingTransformersMultiple Languages

DeepSeek-R1-0528 is a minor version upgrade of the DeepSeek R1 model. It significantly improves the reasoning ability through increased computing resources and algorithm optimization, and performs excellently in multiple benchmark evaluations such as mathematics, programming, and general logic.

Natural Language ProcessingTransformers

The DeepSeek R1 model has undergone a minor version upgrade, with the current version being DeepSeek-R1-0528. In the latest update, DeepSeek R1 significantly enhanced its deep reasoning and inference capabilities by increasing computational resource investment and introducing algorithmic optimization mechanisms during the post-training phase.

Natural Language ProcessingTransformers

Gazal - R1 - 32B is a language model specifically designed for medical reasoning and clinical decision - making. It is built on Qwen 3 32B and demonstrates excellent performance in the professional medical field.

Natural Language ProcessingTransformers

ThinkPRM-7B is a generative process reward model based on the R1-Distill-Qwen-7B architecture, specifically designed for step-by-step verification of inference processes. It evaluates the correctness of each step in reasoning tasks such as mathematical problem-solving and code generation by generating explicit verification thought chains, featuring high data efficiency and strong interpretability.

Natural Language ProcessingTransformersOther

DeepSeek - R1T - Chimera is a high-quality large language model. Through the advanced quantization scheme provided by ik_llama.cpp, it significantly reduces memory usage while maintaining performance.

Natural Language ProcessingGgufOther

R1-Code-Interpreter is the first framework that uses multi-round supervised fine-tuning and reinforcement learning to train large language models for step-by-step code reasoning. It supports 144 different reasoning and planning tasks, enabling the model to autonomously decide when and how to invoke code.

Natural Language ProcessingTransformers

ThinkPRM-1.5B is a generative process reward model based on the R1-Distill-Qwen-1.5B architecture, capable of step-by-step verification of reasoning processes by generating verification chains of thought.

Natural Language ProcessingTransformersOther

OctoThinker-3B-Hybrid-Zero is a reinforcement learning-based language model built on the Llama-3 family and trained using R1-Zero style reinforcement learning techniques.

Natural Language ProcessingSafetensorsEnglish

Fathom-R1-14B is a project based on the R1-distilled-14B model, achieving o4-mini level mathematical reasoning ability under a 16K context with a low training cost of $499.

Natural Language ProcessingTransformers

A Russian news named entity recognition model fine-tuned based on RuBERT-tiny2, focusing on identifying various entities from Russian news texts.

Natural Language ProcessingPytorchrussian

VLAA-Thinker is an innovative vision-language model that can process both image and text inputs simultaneously and generate high-quality text outputs. This model is developed based on the research results of the paper 'SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language Models' and focuses on R1-like reasoning abilities.

MultimodalTransformers