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AI Models 84753

• TheTop-5x7B-Instruct-S5-v0.1-GGUF↗

  MaziyarPanahi

• Velara-Mistral-7B-Instruct-v0.2-slerp-GGUF↗

  MaziyarPanahi

• Atlas-Chat-9B↗

  MBZUAI-Paris

• Ornith-1.5-9B-OBLITERATED↗

  minte1431

• MiniCPM5-2B-8bit↗

  mlx-community

• Qwen3.5-2B-MLX-4bit↗

  mlx-community

  This model was converted using `mlx-vlm` from the `pc/fix-qwen35-predicate` branch, which includes fixes for Qwen3.5 model support (proper handling of MoE gate layers, `shared_expert_gate`, and `A_log` casting). A better, more optimized conversion may be available from **@Prince** (@Blaizzy) in the MLX VLM community. Check the mlx-community organization for updated versions as official Qwen3.5 support is merged into the main `mlx-vlm` branch.

• xtremedistil-l6-h256-zeroshot-v1.1-all-33↗

  MoritzLaurer

  This model was fine-tuned using the same pipeline as described in the model card for MoritzLaurer/deberta-v3-large-zeroshot-v1.1-all-33 and in this paper. The foundation model is microsoft/xtremedistil-l6-h256-uncased. The model only has 22 million backbone parameters and 30 million vocabulary parameters. The backbone parameters are the main parameters active during inference, providing a significant speedup over larger models. The model is 25 MB small. This model was trained to provide a very small and highly efficient zeroshot option, especially for edge devices or in-browser use-cases with transformers.js.

• AlchemistCoder-DS-6.7B-GGUF↗

  mradermacher

• ANIMA-Phi-Neptune-Mistral-10.7B-GGUF↗

  mradermacher

• Darkest-muse-v1-lorablated-v2-i1-GGUF↗

  mradermacher