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AI モデル 84755
- Vero-Qwen3T-8B-i1-GGUF↗
mradermacher
- Wicked-Stuff-12B-i1-GGUF↗
mradermacher
If you are unsure how to use GGUF files, refer to one of TheBloke's READMEs for more details, including on how to concatenate multi-part files. (sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants) And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9
- AB1↗
Muhammadaqib12
- NAMAA-Saudi-TTS-V2↗
NAMAA-Space
- v6-goldfish-250mb-25k-lower-shared-deu-ell-sequential_interleaved↗
nikitastheo
- PIIP-LLaVA_ConvNeXt-L_CLIP-L_1024-336_13B↗
OpenGVLab
- OpenMed-NER-BloodCancerDetect-PubMed-v2-109M↗
OpenMed
**Specialized model for Clinical Entity Recognition - Clinical entities related to Chronic Lymphocytic Leukemia** This model is a **state-of-the-art** fine-tuned transformer engineered to deliver **enterprise-grade accuracy** for clinical entity recognition - clinical entities related to chronic lymphocytic leukemia. 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 CLL dataset - **Production-Ready**: Validated on clinical benchmarks - **Easy Integration**: Compatible with Hugging Face Transformers ecosystem
- tiny-random-olmo-hf↗
optimum-intel-internal-testing
- Qwen3-8B-UserRL-Agent↗
phanviethoang1512
- parrot_fluency_model↗
prithivida