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AI 模型 84760

• frisky-90m↗

  netsrik

• Cosmos-Reason2-2B↗

  NVIDIA

• KVzap-linear-Qwen3-32B↗

  NVIDIA

• lahgtna-omnivoice-v2↗

  oddadmix

• Ornith-1.5-35B-MaxQuality-MTP-GGUF↗

  offmonreal

• GPT-5.6 Terra (Low)↗

  OpenAI

• MiniCPM-V-4.6-BNB↗

  openbmb

  > **This repository hosts the bitsandbytes (NF4, 4-bit) quantized version of MiniCPM-V 4.6.** For the original BF16 weights and the full model card, please refer to openbmb/MiniCPM-V-4.6. A Pocket-Sized MLLM for Ultra-Efficient Image and Video Understanding on Your Phone * [2026.05.17] ⭐️⭐️⭐️ We release the API service of MiniCPM-V 4.6, with a **public free API key** together! Try it now.

• RLPR-Llama3.1-8B-Inst↗

  openbmb

• OpenMed-ZeroShot-NER-Organism-Medium-209M↗

  OpenMed

  **Specialized model for Species Entity Recognition - Species names from the Species-800 dataset** Optimized for **species identification** in scientific text, covering a wide range of taxa and naming variants.Useful for **ecology studies**, **organism tagging**, and **biocuration**. 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.

• tiny-random-qwen-image↗

  optimum-intel-internal-testing