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AI 模型 84760
- gr00t17-lerobot-libero_goal-640↗
NVIDIA
- NV-JEPA-DNA-NTv3↗
NVIDIA
- NV-Segment-CTMR↗
NVIDIA
- stt_it_conformer_transducer_large↗
NVIDIA
- OpenMed-NER-OncologyDetect-SuperClinical-141M↗
OpenMed
This model is a **state-of-the-art** fine-tuned transformer engineered to deliver **enterprise-grade accuracy** for cancer genetics - cancer-related genetic entities. 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 BIONLP2013_CG dataset - **Production-Ready**: Validated on clinical benchmarks - **Easy Integration**: Compatible with Hugging Face Transformers ecosystem - `B-Amino_acid` - `B-Anatomical_system` - `B-Cancer` - `B-Cell` - `B-Cellular_component`
- OpenMed-NER-ProteinDetect-ElectraMed-335M↗
OpenMed
**Specialized model for Biomedical Entity Recognition - Various biomedical entities** This model is a **state-of-the-art** fine-tuned transformer engineered to deliver **enterprise-grade accuracy** for biomedical entity recognition - various biomedical entities. 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 FSU dataset - **Production-Ready**: Validated on clinical benchmarks - **Easy Integration**: Compatible with Hugging Face Transformers ecosystem
- OpenMed-NER-ProteinDetect-MultiMed-568M↗
OpenMed
**Specialized model for Biomedical Entity Recognition - Various biomedical entities** This model is a **state-of-the-art** fine-tuned transformer engineered to deliver **enterprise-grade accuracy** for biomedical entity recognition - various biomedical entities. 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 FSU dataset - **Production-Ready**: Validated on clinical benchmarks - **Easy Integration**: Compatible with Hugging Face Transformers ecosystem
- PP-OCRv6_medium_rec_safetensors↗
PaddlePaddle
- Canopus-LoRA-Flux-UltraRealism-2.0↗
prithivMLmods
- inclusionAI-ZwZ2-9B-GGUF↗
prithivMLmods