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AI モデル 84999

• NemoGuard-JailbreakDetect↗

  NVIDIA

• gpt-4o-search-preview↗

  OpenAI

• OpenMed-ZeroShot-NER-Genome-Base-220M↗

  OpenMed

  **Specialized model for Gene/Protein Entity Recognition - Gene and protein mentions** Accurate **gene/protein mention recognition**, including synonyms and symbol variants from biomedical literature.Enables **gene-centric curation**, **variant/association mining**, and **network construction**. OpenMed ZeroShot NER is an advanced, domain-adapted Named Entity Recognition (NER) model designed specifically for medical, biomedical, and clinical text mining. Leveraging state-of-the-art zero-shot learning, this model empowers researchers, clinicians, and data scientists to extract expert-level biomedical entities—such as diseases, chemicals, genes, species, and clinical findings—directly from unstructured text, without the need for task-specific retraining.

• OpenResearcher-30B-A3B↗

  OpenResearcher

• DeepSeek-V4-Flash-0731-gguf-ds4↗

  ox-ox

  GGUF builds of **deepseek-ai/DeepSeek-V4-Flash-0731** (the official release of DeepSeek V4 Flash: 304B total parameters, hybrid CSA+HCA attention, 1M context) for the **ds4 / DwarfStar** inference engine. Runs fully resident on a single 128 GB Apple Silicon machine. Quantized in the asymmetric style of antirez/deepseek-v4-gguf: crush the routed experts (they are almost all of the weights), keep the decision-making parts high precision. **The filename is the spec.** > 📊 **The imatrix is published here too**, not just the models it produced: > `imatrix/DeepSeek-V4-Flash-0731-chat-v2-routed-moe-ds4-1p5m.dat` > (430 MB), collected **on the `0731` weights themselves**, 2729 prompts / 1.5M tokens / > 387M routed-expert observations, 129 entries (43 layers × gate/up/down, full coverage, > zero missing tensors). Reuse it with `deepseek4-quantize --imatrix` to build your own > mix, or to check mine.

• gpt-oss-20b-heretic↗

  p-e-w

• spec-decoding-subfolder-fixture↗

  poolside

  A **tiny, randomly-initialised** Llama pair for exercising *subfolder* loading of a speculative draft model. It exists so inference engines can test the code path in CI without downloading a real checkpoint. A Hugging Face repo id may contain **at most one `/`**, so `org/repo/DFlash` is not a valid id and cannot be passed as a single string. A draft bundled inside its target's repository therefore has to be addressed as a repo id *plus* a separate sub-path, which most engines have no parameter for. This matters in practice: shipping a draft inside its target repo keeps the pair versioned together and downloadable in one fetch, rather than as two repos that can drift apart.

• OneDecision-VisionGuard-9B-SFT-GGUF↗

  prithivMLmods

• USER2-1C-code↗

  PruhaNLP

• Eleusis-12B-GGUF↗

  PygmalionAI