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AI 모델 85003
- Sovereign-0.1-72B-i1-GGUF↗
mradermacher
- SRFT-Qwen2.5-Math-7B-i1-GGUF↗
mradermacher
- SummLlama3.1-8B-i1-GGUF↗
mradermacher
- TowerInstruct-13B-v0.1-EN2ES-i1-GGUF↗
mradermacher
- trinart_stable_diffusion_v2↗
naclbit
- nomic-embed-vision-v1.5↗
nomic-ai
`nomic-embed-vision-v1.5` is a high performing vision embedding model that shares the same embedding space as nomic-embed-text-v1.5. The easiest way to get started with Nomic Embed is through the Nomic Embedding API. For more information, see the API reference
- SWE-Gym-OpenHands-7B-Agent↗
NovaSky-AI
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- Aegis-AI-Content-Safety-LlamaGuard-Defensive-1.0↗
NVIDIA
- diffusers-cd_bedroom256_l2↗
OpenAI
- OpenMed-ZeroShot-NER-Genomic-XLarge-770M↗
OpenMed
Targets **gene and genetics entities**, handling symbol/name variants commonly found in genomics literature.Useful for **genetic association studies**, **variant curation**, and **genomics informatics**. 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. Built on the robust GLiNER architecture and fine-tuned on curated biomedical corpora, OpenMed ZeroShot NER delivers high-precision entity recognition for critical healthcare and life sciences applications. Its zero-shot capability means you can flexibly define and extract any entity type relevant to your workflow, from standard biomedical categories to custom clinical concepts, supporting rapid adaptation to new research domains and regulatory requirements.