llm local low-code no-code itsbrads published0.0.22•a month agopublished version0.0.22,a month ago M Q P Maintenance: 33%.Quality: 35%.Popularity: 2%. superlocal Your local environment, supercharged by ChatGPT. ChatGPT AI local ...
natural-language-processingtext-generationtransformerllamaquantizationmodel-compressionefficient-inferencepost-training-quantizationlarge-language-modelsllmsmall-modelslocalllm UpdatedAug 13, 2024 Python SqueezeAILab/KVQuant Star302 Code Issues Pull requests ...
Llama.cpp is an open-source library and framework. Through CUDA — the NVIDIA software application programming interface that enables developers to optimize forGeForce RTXandNVIDIA RTX GPUs— provides Tensor Core acceleration for hundreds of models, including popularlarge language models(LLMs) like Gemm...
グラボを持っていなくてもCPUでもそれなりに動くLLMモデルがありますし、好きなだけ自分の好きなアバターとお話しても、かかるのは電気代だけです。ですので、気のすむまでお話してみてください。 自分好みにアバターをカスタムしたい場合は、少し前に書いて若干古くなってしまいました...
natural-language-processing compression text-generation transformer llama quantization mistral model-compression efficient-inference efficient-model large-language-models llm small-models localllm localllama Updated Aug 13, 2024 Python BrutalCoding / aub.ai Sponsor Star 198 Code Issues Pull requests Discus...
LocalAI是一个符合 OpenAI API 规范的 REST API,用于本地推理。它允许您在消费级硬件上本地或本地运行 LLMs(不仅仅是)支持多个与 ggml 格式兼容的模型系列。不需要 GPU。 有关支持的模型系列列表,请参见模型兼容性表[5]。 简而言之: •本地的 OpenAI 替代 REST API。您拥有自己的数据。•不需要 GPU...
We’ll explore three powerful tools for running LLMs directly on your Mac without relying on cloud services or expensive subscriptions. Whether you are a beginner or an experienced developer, you’ll be up and running in no time. This is a great way to evaluate different open-source models ...
Welcome to the exciting world of local Large Language Models (LLMs) where we’re pushing the boundaries of what’s possible with AI. Today let’s talk about a cool topic: run models locally, especially on devices like the Raspberry Pi 5. Let’s dive into the future of...
In this blog post, we have seen how easy it is to build a LLM application with Flowise and LocalAI without the need to use any code. This is a great way to quickly prototype and test different LLM models and workflows. We have also seen how easy it is to deploy the infrastructure ...
docker run -it -p 7860:7860 --platform=linux/amd64 -e HUGGING_FACE_HUB_TOKEN="YOUR_VALUE_HERE" local-llm:v1 python app.py Next, open the browser and go tohttp://localhost:7860to see local LLM Docker container output (Figure 3). ...