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The **mmangkad/Qwen3.6-27B-NVFP4** model is a quantized version of Alibaba's Qwen3.6-27B model, an auto-regressive language model that uses an optimized transformer architecture. For more information on the base model, please check here. This model was quantized using the NVIDIA Model Optimizer. This model is built upon a third-party base model; see the link to the Non-NVIDIA (Qwen3.6-27B) Model Card for original requirements and use cases. Developers looking to take off-the-shelf, pre-quantized models for deployment in AI Agent systems, chatbots, RAG systems, and other AI-powered applications.

Text generation
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vit-plant

mmdlqml

This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

Image classification
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This model is a XLM-Roberta-large model fine-tuned for Named Entity Recognition (NER) over the Spanish portion of the CoNLL-2002 dataset. Evaluating it over the test subset of this dataset, we get a F1-score of 89.17, being one of the best NER for Spanish available at the moment.

Text analysis
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LLM-AI-Server

mmkurodan

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