Search FoxAI
AI Models 84753
- toffee-3b-beta-GGUF↗
mradermacher
- Tsunami-1.0-14B-Instruct-GGUF↗
mradermacher
- uzbek-llama-3.1-8B-instruct-v2-GGUF↗
mradermacher
- ViGoRL-7b-Spatial-GGUF↗
mradermacher
- Xiangxin-2XL-Chat-1048k-Chinese-Llama3-70B-i1-GGUF↗
mradermacher
- Llama-3.2-1B-SQL↗
NotebookML
- DeepHermes-3-Mistral-24B-Preview-GGUF↗
NousResearch
- NVIDIA-Nemotron-3.5-Bolt-E4B-BF16↗
NVIDIA
**NVIDIA-Nemotron-3.5-Bolt-E4B-BF16** is a small language model (SLM) further post-trained from Gemma-4-E4B-it by NVIDIA. This is the full-precision (BF16) release. 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 Q4_K_M quantized version, see NVIDIA-Nemotron-3.5-Bolt-E4B-4GB. 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.
- stt_en_fastconformer_ctc_xxlarge↗
NVIDIA
- OpenMed-NER-ChemicalDetect-TinyMed-65M↗
OpenMed
**Specialized model for Chemical Entity Recognition - Identifies chemical compounds and substances in biomedical literature** This model is a **state-of-the-art** fine-tuned transformer engineered to deliver **enterprise-grade accuracy** for chemical entity recognition - identifies chemical compounds and substances in biomedical literature. 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. BC4CHEMD is a biomedical NER corpus for chemical entity recognition from the BioCreative IV challenge.