The recent launch of LLaMA-Mesh marks a significant advancement in the integration of 3D mesh generation with large language models (LLMs). This innovative model allows users to input and generate 3D meshes by representing them as text, thereby unifying 3D and text modalities within a single framework. The model retains the language capabilities of LLMs while enabling conversational 3D creation and mesh understanding. Additionally, the Hyperstack LLM Inference Toolkit has been open-sourced, simplifying workflows for developers and researchers by providing automated model deployment and API management. The toolkit's launch coincides with the release of tutorials for deploying Stable Diffusion 3.5 and Qwen 2.5 Coder 32B, as well as insights into GPU-as-a-Service (GPUaaS). Both LLaMA-Mesh and the Hyperstack toolkit represent significant steps forward in the fields of AI and machine learning.
🏷️:GaussianAnything: Interactive Point Cloud Latent Diffusion for 3D Generation 🔗:https://t.co/wYukbs2Q31 https://t.co/HebW2F7x7c
LLaMA-Mesh: Unifying 3D Mesh Generation with Language Models https://t.co/yF5Fth5eo3 https://t.co/XDGR4osvyj
Llama-Mesh is pretty great at generating 3D meshes. Try it here: https://t.co/bjqF2zkueT