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AI Models 84760

• flammenai_-_flammen15X-mistral-7B-gguf↗

  RichardErkhov

• nbeerbower_-_Stella-mistral-nemo-12B-gguf↗

  RichardErkhov

• simonycl_-_llama-3.1-8b-instruct-ultrafeedback-agg-judge-gguf↗

  RichardErkhov

• HeartMuLa-GGUF↗

  scragnog

• stsb-bert-tiny-safetensors↗

  sentence-transformers-testing

  This is a sentence-transformers model: It maps sentences & paragraphs to a 128 dimensional dense vector space and can be used for tasks like clustering or semantic search. Using this model becomes easy when you have sentence-transformers installed: Without sentence-transformers, you can use the model like this: First, you pass your input through the transformer model, then you have to apply the right pooling-operation on-top of the contextualized word embeddings.

• TriLM_560M_Unpacked↗

  SpectraSuite

• NVIDIA-Nemotron-3.5-Lightning-30B-A3B-MLX-4bit↗

  TensorFold

  A native Apple-silicon conversion of nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16 , quantized with stock 4-bit affine weights and packaged for MLX-LM and oMLX. This repository contains a stock 4-bit affine MLX conversion of NVIDIA Nemotron 3.5 Lightning. The source is a 30B-total / 3B-active hybrid mixture-of-experts model that interleaves Mamba-2, sparse MoE, and attention layers. The upstream tokenizer, chat template, and generation configuration are preserved. The decode figure is the median of three greedy 256-token runs after a 32-token Metal-kernel warm-up. It is a practical local reference, not a controlled cross-platform benchmark. Prompt length, context growth, sampler settings, memory pressure, thermal state, and MLX/oMLX versions can materially change performance.

• leo-hessianai-7B-chat-bilingual-GGUF↗

  TheBloke

• WestLake-7B-v2-GGUF↗

  TheBloke

• TinyLlama-1.1B-Chat-v0.2-GGUF↗

  TinyLlama