Quick overview of LLM MLX LORA training parameters. weight_decay A regularization technique that adds a small penalty to the weights during training to prevent them from growing too large, helping to reduce overfitting. Often implemented as L2 regularization.examples: 0.00001 – 0.01 grad_clip Short for gradient clipping — a method that limits (clips) the size of gradients during backpropagation to prevent exploding gradients and stabilize training.examples: 0.1 – 1.0 rank Refers to the dimensionality or the number of independent directions in a matrix or tensor. In low-rank models, it controls how much the model compresses or approximates the original data.examples: 4,
Full fine-tuning of mlx-community/Qwen2.5-3B-Instruct-bf16 Recently I posted article on how to train LORA MLX LLM here. Then I asked myself how can I export or convert such MLX model into HF or GGUF format. Even that MLX has such option to export MLX into GGUF most of the time it is not supported by models I have been using. From what I recall even if it does support Qwen it is not version 3 but version 2 and quality suffers by such conversion. Do not know why exactly it works like that. So I decided to give a try with
I have done over 500 training sessions using Qwen2.5, Qwen3, Gemma and plenty other LLM publicly available to inject domain specific knowledge into the model’s low rank adapters (LORA). However, instead of giving you tons of unimportant facts I will just stick to the most important things. Starting with the fact that I have used MLX on my Mac Studio M2 Ultra as well as on MacBook Pro M1 Pro. Both fit well to this task in terms of BF16 speed as well as unified memory capacity and speed (up to 800GB/s). Memory speed is the most important factor comparing
During sync between two Proxmox Backup Server instances I got “decryption failed or bad record mac” error message. So I decided to go for upgrading source PBS to match its version with target PBS. PBS upgrade To upgrade PBS: Get rid of bookworm sources. And then: However it did not help. Further debugging 3 things involved in this investigation. This one: Next disabling Suricata IDS/ISP. Did not help. Finally I changed pfSense settings for System – Advanced – Firewall & NAT from Aggressive to Conservative: It worked.
Add “alias” to /etc/network/interfaces: And restart network interfaces.
YOLOX is an anchor-free version of YOLO, with a simpler design but better performance! It aims to bridge the gap between research and industrial communities. For more details, please refer to our report on Arxiv. https://yolox.readthedocs.io/en/latest/demo/onnx_readme.html https://github.com/Megvii-BaseDetection/YOLOX/tree/main/demo/ONNXRuntime To configure this in Frigate:
You can use either –query-gpu option: Example output: Or dmon: Example output: With little explanation:
Imaging you are running TrueNAS virtualized and would like to resize drive increasing its capacity. Then reboot and new size should be visible in ZFS pool. It has ability to auto expand by default.
Upload image, enter text prompt and press Start Generation. It is as easy as it looks like. So we take some pre-trained models, feed it with some text prompt and starting image and things happen on GPU side to generate frame by frame and merge it into motion picture. It is sometimes funny, creepy but every time it is interesting to see live coming into still pictures and making video out of them. User Interface On the left you upload starting image and write prompt below it describing what it should look like in video output. Once started, do to