unsloth-models
Unsloth supports a wide range of state-of-the-art model architectures, providing pre-quantized Hub variants and optimized kernels for models like Llama 4, DeepSeek-R1, and Qwen3. Selecting the right variant (Instruct vs Base) is critical for training success.
npx skills add majiayu000/claude-skill-registry --skill unsloth-models --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
--- name: unsloth-models description: Guidance on selecting and configuring supported model architectures like Llama 4, DeepSeek-R1, and Qwen3. Triggers: llama 4, deepseek-r1, qwen3, gemma 3, model selection, instruct vs base. --- ## Overview Unsloth supports a wide range of state-of-the-art model architectures, providing pre-quantized Hub variants and optimized kernels for models like Llama 4, DeepSeek-R1, and Qwen3. Selecting the right variant (Instruct vs Base) is critical for training success. ## When to Use - When starting a new fine-tuning project and deciding on a base architecture. - When utilizing reasoning-heavy models (DeepSeek-R1) on consumer hardware. - When performing continued pre-training on domain-specific data. ## Decision Tree 1. Is the task conversational or instruction-following? - Yes: Use 'Instruct' variants. 2. Is the task raw knowledge injection or domain pre-training? - Yes: Use 'Base' variants. 3. Is reasoning/logic a priority? - Yes: Select DeepSeek-R1 Distills or similar architectures. ## Workflows ### Selecting the Right Model 1. Use 'Instruct' models for conversational tasks or when data is limited. 2. Use 'Base' models for domain-specific knowledge i
- Overview
- When to Use
- Decision Tree
- Workflows
- Selecting the Right Model
- Fine-tuning DeepSeek-R1 Distills
- Non-Obvious Insights
- Evidence
- Scripts
- Dependencies
- References
What does the unsloth-models skill do?
Unsloth supports a wide range of state-of-the-art model architectures, providing pre-quantized Hub variants and optimized kernels for models like Llama 4, DeepSeek-R1, and Qwen3. Selecting the right variant (Instruct vs Base) is critical for training success.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill unsloth-models --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.