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AI Models 84757

• thkim0305_-_Mistral-7B_ours_algo7s_lyr20_n11_0.5_0.5_0.1_0.1_200steps_full-gguf↗

  RichardErkhov

• Llama-xLAM-2-8b-fc-r-gguf↗

  Salesforce

  This repo provides the GGUF format for the Llama-xLAM-2-8b-fc-r model. Here's a link to original model Llama-xLAM-2-8b-fc-r. Large Action Models (LAMs) are advanced language models designed to enhance decision-making by translating user intentions into executable actions. As the **brains of AI agents**, LAMs autonomously plan and execute tasks to achieve specific goals, making them invaluable for automating workflows across diverse domains. **This model release is for research purposes only.** The new **xLAM-2** series, built on our most advanced data synthesis, processing, and training pipelines, marks a significant leap in **multi-turn conversation** and **tool usage**. Trained using our novel APIGen-MT framework, which generates high-quality training data through simulated agent-human interactions. Our models achieve state-of-the-art performance on **BFCL** and **τ-bench** benchmarks, outperforming frontier models like GPT-4o and Claude 3.5. Notably, even our smaller models demonstrate superior capabilities in multi-turn scenarios while maintaining exceptional consistency across trials.

• xLAM-1b-fc-r-gguf↗

  Salesforce

• YuE2-GGUF↗

  scragnog

  GGUF conversions of m-a-p/YuE2-3B and m-a-p/YuE2-Vae for HOT-Step CPP, a local C++/GGML music generation engine. YuE2 is an autoregressive-planner + flow-matching music model from the M-A-P team; these files let it run through HOT-Step's GGML inference stack instead of the original PyTorch checkpoint. - Size: 3,960,938,800 bytes. - SHA256: `96fe199377309001ed8cd26a944baeee8cc31a20ba7c36d1d3c0a7e1f4149db6`. - No changes to the upstream checkpoint; the upstream CC BY-NC 4.0 licence applies. See LICENSE. All model weights here are derived from the original YuE2 release. Credit and thanks to the YuE2 authors (M-A-P) for the underlying research and checkpoints:

• A.X-4.0-Light↗

  skt

  SK Telecom released **A.X 4.0** (pronounced "A dot X"), a large language model (LLM) optimized for Korean-language understanding and enterprise deployment, on July 03, 2025. Built on the open-source Qwen2.5 model, A.X 4.0 has been further trained with large-scale Korean datasets to deliver outstanding performance in real-world business environments. - **Superior Korean Proficiency**: Achieved a score of 78.3 on KMMLU, the leading benchmark for Korean-language evaluation and a Korean-specific adaptation of MMLU, outperforming GPT-4o (72.5). - **Deep Cultural Understanding**: Scored 83.5 on CLIcK, a benchmark for Korean cultural and contextual comprehension, surpassing GPT-4o (80.2). - **Efficient Token Usage**: A.X 4.0 uses approximately 33% fewer tokens than GPT-4o for the same Korean input, enabling more cost-effective and efficient processing. - **Deployment Flexibility**: Offered in both a 72B-parameter standard model (A.X 4.0) and a 7B lightweight version (A.X 4.0 Light). - **Long Context Handling**: Supports up to 131,072 tokens, allowing comprehension of lengthy documents and conversations. (Lightweight model supports up to 16,384 tokens length) Benchmarks A.X 4.0 Qwen3-235B-A22B (w/o reasoning) Qwen2.5-72B GPT-4o

• stable-diffusion-3.5-medium-amdnpu↗

  Stability AI

• suno-act-tags↗

  Suno

• Huihui-Qwen3.8-27B-abliterated-INT4-AWQ-GPTQ↗

  TelperionAI

• gemma-3-27b-it-uncensored-mlx-4bit↗

  TheCluster

• GLM-5.3-Flash-VQ-3.6bpw↗

  TheDrainFlorist