Rehan Wazir
RehanWazir
AI & ML interests
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Recent Activity
replied to
davanstrien's
post
5 days ago
Inspired by Hugging Face's official MCP server, I've developed a complementary tool that exposes my semantic search API to enhance discovery across the HF platform.
Key capabilities:
- AI-powered semantic search for models and datasets
- Parameter count analysis via safetensors metadata
- Trending content discovery
- Find similar models/datasets functionality
- 11 tools total for enhanced ecosystem navigation
The semantic search goes beyond simple keyword matching, understanding context and relationships between different models and datasets.
Example query: "Find around 10 reasoning Hugging Face datasets published in 2025 focusing on topics other than maths and science. Show a link and a short summary for each dataset." (results in video!)
https://github.com/davanstrien/hub-semantic-search-mcp
replied to
MaziyarPanahi's
post
5 days ago
𧬠Breaking news in Clinical AI: Introducing the OpenMed NER Model Discovery App on Hugging Face π¬
OpenMed is back! π₯ Finding the right biomedical NER model just became as precise as a PCR assay!
I'm thrilled to unveil my comprehensive OpenMed Named Entity Recognition Model Discovery App that puts 384 specialized biomedical AI models at your fingertips.
π― Why This Matters in Healthcare AI:
Traditional clinical text mining required hours of manual model evaluation. My Discovery App instantly connects researchers, clinicians, and data scientists with the exact NER models they need for their biomedical entity extraction tasks.
π¬ What You Can Discover:
β
Pharmacological Models - Extract "chemical compounds", "drug interactions", and "pharmaceutical" entities from clinical notes
β
Genomics & Proteomics - Identify "DNA sequences", "RNA transcripts", "gene variants", "protein complexes", and "cell lines"
β
Pathology & Disease Detection - Recognize "pathological formations", "cancer types", and "disease entities" in medical literature
β
Anatomical Recognition - Map "anatomical systems", "tissue types", "organ structures", and "cellular components"
β
Clinical Entity Extraction - Detect "organism species", "amino acids", 'protein families", and "multi-tissue structures"
π‘ Advanced Features:
π Intelligent Entity Search - Find models by specific biomedical entities (e.g., "Show me models detecting CHEM + DNA + Protein")
π₯ Domain-Specific Filtering - Browse by Oncology, Pharmacology, Genomics, Pathology, Hematology, and more
π Model Architecture Insights - Compare BERT, RoBERTa, and DeBERTa implementations
β‘ Real-Time Search - Auto-filtering as you type, no search buttons needed
π¨ Clinical-Grade UI - Beautiful, intuitive interface designed for medical professionals
Ready to revolutionize your biomedical NLP pipeline?
π Try it now: https://huggingface.co/spaces/OpenMed/openmed-ner-models
𧬠Built with: Gradio, Transformers, Advanced Entity Mapping
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