Tested MinishLab/semble on a 1595-md Astro blog: warm bm25 returns symbol definitions in 0.84s, hybrid mode loses `seasonalBanner` to the article corpus.
Tested on M1 Max 64GB ComfyUI: Anima-Base v1.0 matches preview3-base in speed; WAI-Anima kana LoRA hits 22% on light prompts but 67% with hood+robe+embroidery added.
From v2 to v3 of Kana Chat, an AI agent built around official CLI wrappers. The story of stepping back from the DIY OpenClaw direction and pivoting toward a blog pipeline that quickly drafts the daily flood of AI news and papers.
Took 53 cleaned images prepared for WAI-IL and trained a WAI-Anima character LoRA with AnimaLoraToolkit + RunPod. Training itself ran for $1.22, but at inference the side ponytail direction wouldn't shift with Danbooru tags or natural language. Verification record showing the issue is a directional bias inherited from Anima base (preview3-base onward).
I dropped the nervous sample identified as the culprit last time, plus 5 others, and retrained the LoRA under otherwise identical conditions. The sweat drops on ep08 angry are gone, and as a bonus, ep06 produced the closed-mouth restrained anger that the previous training never managed to reproduce.
Training an Illustrious-XL LoRA on RunPod for around $1 by doing env setup on a $0.08/hr CPU Pod and renting the 4090 only for actual training. Network Volumes attach to both pods at the same time, so there's no idle GPU billing. Four sd-scripts gotchas hit on the way included.
Hands-on running inclusionAI Ling-flash-2.0 (100B / 6.1B active, MXFP4 quant, 54.7GB) on SwiftLM via mlx-swift-lm on an M1 Max 64GB. Covers bailing_moe + MXFP4 support check in mlx-swift, the startup surprise, and what --stream-experts actually saves.
WAI-Illustrious SDXL v17 tested on M1 Max 64GB ComfyUI against v16 with the same seed. Hires fix now auto-corrects hands and feet, the four rating tags (general/sensitive/nsfw/explicit) still drive NSFW output, and v16-trained LoRAs mostly carry over — with one case where they don't.
A hands-on build and run of the Swift-based LLM inference server SwiftLM on an M1 Max 64GB. Covers Qwen3.6-35B-A3B and Qwen3.5-122B-A10B, with the same BST, BBS, and persona tests used in the existing Ollama and MLX-lm write-ups.
Tried Qwen3.6-27B on both Ollama and MLX. Ollama couldn't load the VL-projector-embedded GGUF, MLX ran it at 11 tok/s. On the side, running 35B-A3B under MLX was roughly 2× faster than the Ollama GGUF. Also had both models build a BBS to gauge intent handling.
A hands-on log of Qwen3.6-35B-A3B under Ollama 0.20.6. Generation speed matches Qwen3.5 at 27 tok/s, but thinking tokens grew 13× for the same prompt. Multi-turn, persona, and a three-tier NSFW probe are included.
Z-Image has its own pixel art LoRAs, but can they actually convert photos to pixel art via i2i? Tested Z-Image Turbo, base model, and compared with Illustrious on M1 Max 64GB.
