Download a quant (single GPU VRAM guide: 6.0bpw ≈ 22 GB fits a 24 GB card; 4.0bpw/3.0bpw for smaller cards): We train Ostrich LLMs to bring back knowledge that matters: the kind that helps humans stay healthy, free, and self-reliant. We believe liberating wisdom is missing or underrepresented in today's AI, whether deliberately omitted or simply outnumbered. This model is abliterated: refusal behavior has been removed so you get uncensored, direct answers. We targeted both alignment and some skills in this model. The model has lower instruction following capability than vanilla Qwen 3.8 (it has so much freedom in it, it doesn't obey the user that well:). Current eval method is still close…
Independent publisher
Emin Temiz
etemiz
Alignment
Models in Library2
Datasets in Library0
Models on Hugging Face23
Followers129
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Models
We train Ostrich LLMs to bring back knowledge that matters: the kind that helps humans stay healthy, free, and self-reliant. We believe liberating wisdom is missing or underrepresented in today's AI, whether deliberately omitted or simply outnumbered. This model is abliterated: refusal behavior has been removed so you get uncensored, direct answers. We targeted both alignment and some skills in this model. The model has lower instruction following capability than vanilla Qwen 3.8 (it has so much freedom in it, it doesn't obey the user that well:). Current eval method is still close to AHA 2026. Compared to Qwen 3.8 27B (vanilla) this model looks much more aligned: This model vs vanilla Qwen…