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AI 모델 84757

• llm4decompile-6.7b-v2-Q4_K_M-GGUF↗

  Th3S

• Mistral-7B-Instruct-v0.1-GGUF↗

  TheBloke

  TheBloke's LLM work is generously supported by a grant from andreessen horowitz (a16z) - Model creator: Mistral AI - Original model: Mistral 7B Instruct v0.1 This repo contains GGUF format model files for Mistral AI's Mistral 7B Instruct v0.1.

• vit_so400m_patch14_siglip_378.webli_ft_in1k↗

  timm

• tiny-MistralForCausalLM-0.1↗

  trl-internal-testing

  This is a minimal model built for unit tests in the TRL library.

• Llama-3.1-8B-Instruct-GGUF↗

  unsloth

  The Meta Llama 3.1 collection of multilingual large language models (LLMs) is a collection of pretrained and instruction tuned generative models in 8B, 70B and 405B sizes (text in/text out). The Llama 3.1 instruction tuned text only models (8B, 70B, 405B) are optimized for multilingual dialogue use cases and outperform many of the available open source and closed chat models on common industry benchmarks. **Model Architecture:** Llama 3.1 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align with human preferences for helpfulness and safety. **Llama 3.1 family of models**. Token counts refer to pretraining data only. All model versions use Grouped-Query Attention (GQA) for improved inference scalability.

• Krea-2-Turbo-GGUF↗

  vantagewithai

  **Watch us on Youtube:** @VantageWithAI See our collection of in-house trained LoRAs trained on Raw and meant to be used with Turbo: Krea-2 LoRA Collection - **Model Name:** Krea 2 - **Version:** v1.0 - **Release Date:** June 22, 2026 - **Model Type:** Text-to-image diffusion model - **Architecture:** Diffusion Transformer with 12 billion parameters - **License:** Krea 2 Community License - **Release Format:** Open-weight release and Krea-hosted product integrations - **Model Developer:** Krea.ai, Inc.

• Ebai3.6-27b-unscensored↗

  vathvathv

• InternVL2_5-1B_VQA↗

  yongxianwei

• Ternary-Bonsai-2-27B-MTPLX-Optimized-Speed↗

  Youssofal

  **MTPLX: the fastest way to run Ternary Bonsai 2 27B on a Mac. Native multi-token-prediction speculative decoding on Apple Silicon, exact at any temperature.** Prism ML's Ternary Bonsai 2 27B is Qwen 3.8 27B rebuilt with ternary weights, and Prism ML reports it keeps 98.2 percent of the full model's benchmark average in 8.85 GB. On MTPLX it runs on GPU kernels written for it, with the Qwen 3.8 27B multi-token-prediction head drafting ahead. That makes it faster than the 4-bit Qwen 3.8 27B in half the memory. It reads images, and it runs on a Mac with 16 GB. Prism ML's own figure for Bonsai 2 27B on an M5 Max with MLX is 46.8 tok/s. On MTPLX the same chip decodes it at 64.4 tok/s after a 4,061-token prompt.

• MiniMax-H3-FastH3-v1-dense-datafree-ComfyUI↗

  zerubroberts