AI & Machine Learning
[omh] Making a model smaller or cheaper by changing its weights: quantization (GPTQ, AWQ, GGUF, bitsandbytes, FP8, quantization-aware training), pruning, or distillation into a smaller student, sized to the target hardware, calibrated on the task's own data, and kept only when it holds quality on the person's own eval. Use when the user says: model-compression, model compression, compress this model, compress the model, compress a model, compress our model, compress my model, quantize this model.
Publisher / source
rlaope/oh-my-hermes (found on GitHub top repositories)
Upstream record
Version
Version 1
Published
2026-11-13
Publication review
Approved for publication
Content fingerprint
0be6895dba704545c566c5b9b5ed0a2e90764e317228985442708138f2e7735e
Review before you use it
Publication approval is a recorded review state, not a guarantee of safe execution. Check the upstream license, required tools and permissions, and test in your intended client.
Sign in to inspect the full instructions and download the SKILL.md file. This public page contains metadata only.
Source: https://prompeteer.ai/skills-hub/6382f9e3-86fc-403b-be82-552f2d07a226