The MiMo Embodied Model (MiMo-Embodied) is a powerful cross-embodied vision-language model that has demonstrated excellent performance in both autonomous driving and embodied AI tasks. It is the first open-source vision-language model that combines these two key domains, significantly enhancing the understanding and reasoning abilities in dynamic physical environments.

MultimodalTransformers

MiMo Audio is an audio language model developed by Xiaomi, which demonstrates strong few-shot learning ability through large-scale pre-training. This model breaks through the limitations of traditional models that rely on fine-tuning for specific tasks and performs excellently in tasks such as speech intelligence and audio understanding, reaching an advanced level among open-source models.

Audio ProcessingSafetensors

MiMo Audio is an audio language model based on large-scale pre-training, achieving SOTA performance among open-source models in speech intelligence and audio understanding benchmark tests. This model demonstrates strong few-shot learning ability and can generalize to tasks not included in the training data, supporting various audio tasks such as speech conversion, style transfer, and speech editing.

Audio ProcessingSafetensors

This is a quantized version of XiaomiMiMo's MiMo-VL-7B-SFT-2508 model, optimized using llama.cpp to improve the model's running performance on specific hardware. This model is a vision-language model with 7 billion parameters, supporting image-to-text generation tasks.

MultimodalGguf

This is the GGUF quantized version of the Xiaomi MiMo-VL-7B-RL-2508 model, quantized using the imatrix option of llama.cpp. It supports multiple quantization levels and is suitable for different hardware configurations and performance requirements.

MultimodalGguf

MiMo is a series of large language models trained from scratch by Xiaomi specifically for inference tasks. Through optimizing pre-training and post-training strategies, it demonstrates excellent performance in mathematical and code reasoning tasks. The project has open-sourced multiple versions with a 7B parameter scale, including the base model, SFT model, and RL model.

Natural Language ProcessingTransformers

This is the GGUF quantized version of the XiaomiMiMo/MiMo-VL-7B-RL-2508 model, using the Q6_K quantization level. This model is a multimodal visual language model with a scale of 7B parameters, supporting joint understanding and generation tasks of images and text.

MultimodalTransformers

MiMo-VL is a compact and powerful vision-language model that combines a native resolution ViT encoder, an MLP projector, and the MiMo-7B language model. It performs excellently in tasks such as multimodal reasoning. This model shows outstanding performance in multiple benchmark tests, has a chain-of-thought control function, and significantly improves the user experience.

MultimodalTransformers

MiMo-VL is a compact and powerful vision-language model that combines a native resolution ViT encoder, an MLP projector, and the MiMo-7B language model optimized for complex reasoning tasks. Through multi-stage pre-training and post-training, it has achieved excellent results in multiple vision-language tasks.

MultimodalTransformers

IceBERT-PoS is a pre-trained model specifically designed for Icelandic part-of-speech tagging, built on the IceBERT architecture. This model can perform part-of-speech tagging on each word in an Icelandic sentence and output detailed grammatical attribute information. It supports multiple output formats, including a structured tuple format with high readability and the IFD format compatible with the MIM-GOLD evaluation standard.

Natural Language ProcessingTransformersOther

MiMo is a series of 7B parameter models trained from scratch for inference tasks. Through optimized pre-training and post-training strategies, it performs excellently in mathematical and code reasoning tasks.

Natural Language ProcessingTransformers

MiMo-7B is a language model series launched by Xiaomi, specifically designed for reasoning tasks, including base models, SFT models, and RL models, excelling in mathematical and code reasoning tasks.

Natural Language ProcessingTransformers

MiMo-7B-RL is a reinforcement learning model trained based on the MiMo-7B-SFT model, demonstrating outstanding performance in mathematical and code reasoning tasks, comparable to OpenAI o1-mini.

Natural Language ProcessingTransformers

A 7B-parameter specialized inference language model series launched by Xiaomi, significantly enhancing mathematical and code reasoning capabilities through optimized pre-training and post-training strategies

Natural Language ProcessingTransformers

MiMo-7B-RL is a reinforcement learning model trained based on the MiMo-7B-SFT model, achieving performance comparable to OpenAI o1-mini in mathematical and code reasoning tasks.

Natural Language ProcessingTransformers

ViT reg4 image encoder pretrained with Masked Image Modeling (MIM), suitable for general feature extraction or downstream vision tasks

Computer VisionPytorch

This model is based on BiomedBERT and is used for sentence segmentation of MIMIC-III clinical records, predicting BIO annotations.

Natural Language ProcessingSafetensorsEnglish

A Hiera image encoder employing an absolute window position embedding strategy, pre-trained via Masked Image Modeling (MIM), serving as a general-purpose feature extractor or backbone network for downstream tasks.

Computer VisionPytorch

TxAgent-T1 is a medical intelligent agent model fine-tuned on Llama3.1-8B-Instruct, specializing in personalized treatment recommendations and drug reasoning

Natural Language ProcessingTransformers

Cuckoo is a 300-million-parameter information extraction model that mimics the next-token prediction paradigm of large language models for information extraction, capable of self-enhancement using various text resources.

Natural Language ProcessingTransformers