Chatbot Llama 2 70B – run locally in a jupyter notebook
With this article I would like to help you to run locally under Ubuntu 22.04 Llama 2 in the 70B...
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Author: Maker
AnyLabeling – installation guide and experience report
A lot of data and matching labels are very important for training neural networks. Therefore,...
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oobabooga – text-generation-webui mit Llama 2 – local Installation
I always wanted to try a Llama model of META and with the release of Llama 2 it was then so far...
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YOLOv5 – Optimization of training data for PFM-1 antipersonnel mine detection
After training the first 31 models for anti-personnel mine detection, my data set has grown...
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YOLOv5 – Training a neural network for PFM-1 antipersonnel mine detection
This paper is about training a neural network based on YOLOv5. This YOLO network should be able to...
Read More- Install vLLM on Gigabyte AI TOP ATOM: High-Performance LLM Inference with OpenAI-Compatible API – Part 3-3Download and Run Additional Models Locally Since you already downloaded models locally in Phase 4, you can now switch between different models without having to redownload them. To use another already downloaded model, simply stop the current container and restart it with the desired model. First, I stop the current container (if it is still… Read more: Install vLLM on Gigabyte AI TOP ATOM: High-Performance LLM Inference with OpenAI-Compatible API – Part 3-3
- Install vLLM on Gigabyte AI TOP ATOM: High-Performance LLM Inference with OpenAI-Compatible API – Part 2-3Configuring vLLM for Production Deployment (More Complex) For production use, I want to run the container in the background and ensure that it starts automatically after a reboot. Additionally, I mount the Hugging Face cache so that models do not have to be redownloaded every time the container starts. This saves you the time otherwise… Read more: Install vLLM on Gigabyte AI TOP ATOM: High-Performance LLM Inference with OpenAI-Compatible API – Part 2-3
- Install vLLM on Gigabyte AI TOP ATOM: High-Performance LLM Inference with OpenAI-Compatible API – Part 1-3After showing you how to install Ollama, Open WebUI, ComfyUI, and LLaMA Factory on the Gigabyte AI TOP ATOM in my previous posts, now comes something for everyone who needs maximum performance when running Large Language Models: vLLM – a high-performance inference engine specifically designed to run LLMs with maximum throughput and minimal memory consumption.… Read more: Install vLLM on Gigabyte AI TOP ATOM: High-Performance LLM Inference with OpenAI-Compatible API – Part 1-3
- Installing LLaMA Factory on Gigabyte AI TOP ATOM: Fine-tuning Language Models with LoRA and QLoRA – Part 2-2
Phase 7: Start Fine-Tuning Training Before I start the training, I might need to log in to the Hugging Face Hub if the model is gated (has access restrictions). For public models, this is not necessary: Command: huggingface-cli login You will be asked for your Hugging Face token. You can find this in your Hugging… Read more: Installing LLaMA Factory on Gigabyte AI TOP ATOM: Fine-tuning Language Models with LoRA and QLoRA – Part 2-2 - Installing LLaMA Factory on Gigabyte AI TOP ATOM: Fine-tuning Language Models with LoRA and QLoRA – Part 1-2After showing how to install Ollama, Open WebUI, and ComfyUI on the Gigabyte AI TOP ATOM in my previous posts, now comes something for everyone who wants to adapt their own language models and make them individual: LLaMA Factory – an open-source framework that simplifies the fine-tuning of Large Language Models and supports methods such… Read more: Installing LLaMA Factory on Gigabyte AI TOP ATOM: Fine-tuning Language Models with LoRA and QLoRA – Part 1-2
The tutorial offers a clear and practical guide for setting up and running the Tensorflow Object Detection Training Suite. Could…
This works using an very old laptop with old GPU >>> print(torch.cuda.is_available()) True >>> print(torch.version.cuda) 12.6 >>> print(torch.cuda.device_count()) 1 >>>…
Hello Valentin, I will not share anything related to my work on detecting mines or UXO's. Best regards, Maker
Hello, We are a group of students at ESILV working on a project that aim to prove the availability of…