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AI 모델 84759

• Wicked-Tutu-26B-A4B-i1-GGUF↗

  mradermacher

• zen4-micro-GGUF↗

  mradermacher

• phi-4-14B-grpo-gsm8k-3e-q4↗

  mrm8488

• gemma-4-E4B-it-Heretic-ARA-Refusals3-GGUF↗

  NullpoLab

• cascade_mask_rcnn_mamba_vision_small_3x_coco↗

  NVIDIA

• NVIDIA-Nemotron-3.5-Bolt-E4B-4GB↗

  NVIDIA

  **NVIDIA-Nemotron-3.5-Bolt-E4B-4GB** is a small language model (SLM) further post-trained from Gemma-4-E4B-it by NVIDIA. Nemotron-3.5-Bolt-E4B carries forward Gemma’s strong conversational capabilities and further improves multi-turn tool use, instruction following, and input grounding for fast local voice/device assistants, interactive personas, and embedded/edge interfaces. Designed for low-memory, low-TTFT operation, the model allows agents to respond quickly while preserving headroom for applications or adjacent model pipelines. For speculative decoding, use the companion DFlash drafter. For the full-precision (BF16) version, see NVIDIA-Nemotron-3.5-Bolt-E4B-BF16. NVIDIA Nemotron™ is a family of open models with open weights, training data, and recipes, delivering leading efficiency and accuracy for building specialized AI agents.

• laneformer-2b-it-q4-mlx↗

  OpenMed

• OpenMed-ZeroShot-NER-Species-Tiny-60M↗

  OpenMed

  **Specialized model for Species Entity Recognition - Species and organism names** Specialized in **species and organism mentions** with robust handling of scientific/common names and abbreviations.Applies to **biodiversity mining**, **metagenomics reporting**, and **taxonomy-aware literature curation**. 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.

• Qwen2.5-7B-Instruct-converge-collective-v2↗

  Optitransfer

• Qwen2.5-Math-1.5B-4bit↗

  PowCal

  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed]