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...
LLama2:部署实操体验llama2,基于Hugging Face和LangChain 使用开源 Llama2-13b-chat/Llama2-70b-cha 3414 -- 9:45 App gpt-llm-trainer:一句描述实现数据集生成、llama2微调、合并模型权重等,高效实现特定任务模型微调 5302 10 21:09 App localgpt+vicuna7b+instructor-emb:低固定成本、数据100%安全的本地化微...
voicechat2 A fast, fully local AI Voicechat using WebSockets WebSocket server, allows for simple remote access Default web UI w/ VAD usingricky0123/vad, Opus support usingsymblai/opus-encdec Modular/swappable SRT, LLM, TTS servers SRT:whisper.cpp,faster-whisper, orHF Transformers whisper ...
python run_localGPT.py --save_qa Run the Graphical User Interface Openconstants.pyin an editor of your choice and depending on choice add the LLM you want to use. By default, the following model will be used: MODEL_ID ="TheBloke/Llama-2-7b-Chat-GGUF"MODEL_BASENAME ="llama-2-7b-cha...
做了一个整合功能的LocalLLM | 这两天整合ChatGLM,StableDiffusion,PaddleNLP,PPDiffuser,Paddle-Pipeline等开发了一个全功能的多模态聊天程序,把想到的功能都堆上了。可以根据Prompt聊天、画图、用搜索引擎查询、查询本地的知识库等等。玩了一下午感觉还是很有意思的。
Fortunately, there are ways to run a ChatGPT-like LLM (Large Language Model) on your local PC, using the power of your GPU. The oobabooga text generation webui might be just what you're after, so we ran some tests to find out what it could — and couldn't! — do, which means ...
Llama.cppis a C and C++ based inference engine for LLMs, optimized for Apple silicon and running Meta’s Llama2 models. Once we clone the repository and build the project, we can run a model with: $ ./main -m /path/to/model-file.gguf -p"Hi there!" ...
在AI盛行的当下,我辈AI领域从业者每天都在进行着AIGC技术和应用的探索与改进,今天主要介绍排到github排行榜第二名的一款名为localGPT的应用项目,它是建立在privateGPT的基础上进行改造而成的。 我认为这个项目最大的亮点在于: 1.使用LLM的力量,无需互联网连接,就可以向你的文档提问。100%私密,任何数据都不会离开...
LocalGPT is an open-source project inspired by privateGPT that enables running large language models locally on a user’s device for private use. The originalPrivate GPTproject proposed the idea of executing the entire LLM pipeline natively without relying on external APIs. However, it was limited...
In this tutorial we will create a personal local LLM assistant, that you can talk to. You will be able to record your voice using your microphone and send to the LLM. The LLM will return the answer…