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AI Models 84759

• Magistral-Small-2506-GGUF↗

  Mungert

• flux2-klein-4b-uncensored-text-encoder↗

  nerualdreming

• splade-bert-base-italian-xxl-uncased-cv↗

  nickprock

• DeepHermes 3 - Llama-3.1 8B Preview (Non-reasoning)↗

  Nous Research

• gpt-4o-audio-preview-2025-06-03↗

  OpenAI

• GPT-6 Luna (Low)↗

  OpenAI

• OpenMed-NER-ChemicalDetect-BioMed-109M↗

  OpenMed

  **Specialized model for Chemical Entity Recognition - Identifies chemical compounds and substances in biomedical literature** This model is a **state-of-the-art** fine-tuned transformer engineered to deliver **enterprise-grade accuracy** for chemical entity recognition - identifies chemical compounds and substances in biomedical literature. This specialized model excels at identifying and extracting biomedical entities from clinical texts, research papers, and healthcare documents, enabling applications such as **drug interaction detection**, **medication extraction from patient records**, **adverse event monitoring**, **literature mining for drug discovery**, and **biomedical knowledge graph construction** with **production-ready reliability** for clinical and research applications. - **High Precision**: Optimized for biomedical entity recognition - **Domain-Specific**: Trained on curated BC4CHEMD dataset - **Production-Ready**: Validated on clinical benchmarks - **Easy Integration**: Compatible with Hugging Face Transformers ecosystem

• OpenMed-PII-Italian-BioClinicalModern-Base-149M-v1↗

  OpenMed

  **OpenMed-PII-Italian-BioClinicalModern-Base-149M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection in Italian text**. This model identifies and classifies **54 types of sensitive information** including names, addresses, social security numbers, medical record numbers, and more.

• Qwen3-VL-8B-Instruct-abliterated-v2↗

  prithivMLmods

• ppt-pythia-1b-appendix-structured-seed3408-stage2↗

  qing-yao