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PyTorch library for audio generation including text-to-music (MusicGen) and text-to-sound (AudioGen).
Passed 23 of 23 test cases with the skill, and 18 of 23 without it.
and 6 more in the full report
5 fixed18 passed either way0 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 5 test cases the skill fixed. Same model, same prompt, with and without the skill.
What are two recommended GPU memory optimization practices when running batch audio generation with AudioCraft models on memory-constrained systems?
| Checked | Without skill | With skill |
|---|---|---|
| The response suggests using half precision (fp16) or smaller model variants. | Passed | Passed |
| The response suggests clearing CUDA cache with torch.cuda.empty_cache. | Missed | Passed |
The instructions your model reads when the skill loads.
This skill is repo-local and stays inactive until explicitly activated.
When the original instructions refer to legacy tool names, use these Kheish mappings:
terminal => bashweb_extract => web_fetch, plus web_search when discovery is neededsearch_files => grep_search and glob_searchbrowser_* tools require a browser-capable surfaced tool or MCP; if none is available, use the closest available surface and say so explicitlyWhen the instructions mention local helper files, resolve them from ${KHEISH_SKILL_DIR}.
Comprehensive guide to using Meta's AudioCraft for text-to-music and text-to-audio generation with MusicGen, AudioGen, and EnCodec.
Use AudioCraft when:
Key features:
Use alternatives instead:
test cases passed, vs 18 / 23 without
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