sir-convert-a-lot-qwen-finetuning
Specific fine-tuning workflow for Qwen3-TTS, focusing on Swedish speech data curation and model evaluation.
Install
mkdir -p .claude/skills/sir-convert-a-lot-qwen-finetuning && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/14778" && unzip -o skill.zip -d .claude/skills/sir-convert-a-lot-qwen-finetuning && rm skill.zipInstalls to .claude/skills/sir-convert-a-lot-qwen-finetuning
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Model-specific operator skill for Qwen3-TTS fine-tuning on Hemma and Colab. Use when the task is specifically about Qwen TTS training, Swedish language expansion with Qwen, Qwen preprocessing or runtime policy, or deciding whether a fine-tuned Qwen model should enter the Sir Convert-a-Lot sidecar candidate lane.Key capabilities
- →Fine-tune Qwen3-TTS-12Hz-1.7B-Base model
- →Expand Swedish language support for Qwen
- →Choose between Hemma and Colab H100 for training
- →Manage ROCm, Triton flash attention, or GPU container policy
- →Curate and preprocess Swedish speech data
- →Evaluate trained Qwen models for sidecar candidacy
How it works
This skill manages the fine-tuning process for Qwen3-TTS models, specifically for Swedish language expansion, by guiding infrastructure selection, data preprocessing, and model evaluation.
Inputs & outputs
When to use sir-convert-a-lot-qwen-finetuning
- →Fine-tune Qwen3-TTS for Swedish
- →Preprocess speech corpus data
- →Evaluate speech model performance
- →Configure ROCm or Triton training environments
About this skill
Sir Convert-a-Lot Qwen Finetuning
Use When
- Fine-tuning
Qwen/Qwen3-TTS-12Hz-1.7B-Basefor Swedish. - Working on Qwen preprocessing, training, evaluation, or recovery.
- Choosing between Hemma and Colab for a governed Qwen run.
- Deciding whether Qwen evidence permits promotion into a sidecar candidate lane.
Use the broader .codex/skills/speech-model-finetuning-on-hemma/SKILL.md for
model-agnostic training guidance and
.codex/skills/sir-convert-a-lot-colab-hemma/SKILL.md for Colab/Hemma transfer.
Read Order
references/architecture-and-experiment-contract.mddocs/backlog/epics/epic-sircon-05-qwen3-tts-swedish-language-expansion-fine-tuning-on-hemma-and-colab.mddocs/reference/ref-sircon-research-qwen-training-eval-pilot-progress-ledger-2026-03-15-qwen-training-eval-pilot-progress-ledger-2026-03-15.mddocs/runbooks/run-sircon-qwen3-tts-swedish-finetuning-runbook-for-hemma-and-colab-qwen3-tts-swedish-finetuning-runbook-for-hemma-and-colab.mddocs/decisions/adr-sircon-0005-hemma-sidecar-tts-architecture-and-non-pdf-gpu-governance.mddocs/decisions/adr-sircon-0006-reusable-multi-backend-tts-sidecar-capability-contract.md
The reference owns agent-facing architecture and evidence rules. The runbook owns operator procedure. The progress ledger owns current experiment classes, state vectors, surface status, results, and next-step truth.
Classify First
benchmark: serving and runtime evidence only.single-speaker adaptation: voice-transfer experiments, not general Swedish.language expansion: multi-speaker Swedish support.
Choose language expansion when the requested outcome is general Swedish support.
Workflow
- Confirm the governing backlog slice and the current ledger state.
- Classify the experiment and state its single primary question.
- Check the architecture and evidence contract before changing code or run shape.
- Use the Qwen runbook for commands, host procedure, stop conditions, and recovery.
- Record results and state-vector changes in the progress ledger.
- Promote only through the documented evidence ladder.
Do not copy live operator status, command transcripts, or experiment results into this skill.
When not to use it
- →The task is normal sidecar benchmarking not involving model training
- →The task involves Chatterbox, F5, OpenVoice, or MMS implementation work
- →The task is a generic speech-model training question without Qwen-specific decisions
Limitations
- →The skill is model-specific to Qwen3-TTS
- →The skill is focused on Swedish language expansion
- →The skill is limited to Hemma and Colab H100 for training
How it compares
This skill provides a specialized workflow for Qwen TTS fine-tuning with a focus on Swedish language expansion and specific hardware considerations, unlike general speech model training.
Compared to similar skills
sir-convert-a-lot-qwen-finetuning side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| sir-convert-a-lot-qwen-finetuning (this skill) | 0 | 2mo | No flags | Advanced |
| robotics-code-generator | 14 | 8mo | No flags | Advanced |
| modal | 5 | 8mo | Review | Intermediate |
| hugging-face-cli | 3 | 6mo | Review | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
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