by Aesthisia · Agent Tool · ★ 97
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LLMinator: Run & Test LLMs directly from HuggingFace Gradio based tool with integrated chatbot to locally run & test LLMs directly from HuggingFace. An easy-to-use tool made with Gradio, LangChain, and Torch. ⚡ Features Context-aware Streaming Chatbot. Inbuilt code syntax highlighting. Load any LLM repo directly from HuggingFace. Supports both CPU & CUDA modes. Enable LLM inference with llama.cpp using llama-cpp-python Convert models(Safetensors, pt to gguf etc) Customize LLM inference parameters(ngpulayers, temperature, maxtokens etc) Real-time text generation via websockets, enabling seamless integration with different frontend frameworks. 🚀 Installation To use LLMinator, follow these simple steps: Clone the LLMinator repository from GitHub & install requirements Build LLMinator with llama.cpp: Using : On Linux or MacOS: On Windows: Download the latest fortran version of [w64devkit](
| Stars | 97 |
| Forks | 19 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 39.75/100 |
| Last Updated | 2024-06-27 |
| Created | 2024-03-28 |
| Platforms | browser, python |
| Est. Tokens | ~5k |
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LLMinator is Gradio based tool to run opensource LLM models directly from Huggingface. It is categorized as a Agent Tool with 97 GitHub stars.
LLMinator is primarily written in Python. It covers topics such as chatbot, cpu, cuda.
You can find installation instructions and usage details in the LLMinator GitHub repository at github.com/Aesthisia/LLMinator. The project has 97 stars and 19 forks, indicating an active community.
LLMinator is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to LLMinator on Agent Skills Hub include VT.ai, c4-genai-suite, chainlit_langgraph. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.