Ostrich-27B-Qwen3.5-260411

etemiz/Ostrich-27B-Qwen3.5-260411

Ostrich-27B-Qwen3.5-260411 is a machine learning model from etemiz. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.

Ostrich LLMs, bringing you "the knowledge that matters".

Downloads · 30 days

13% of all-time downloads

All-time downloads

111

Public

Parameters

26.9B

53.8 GB on disk

Likes

Public

Hugging Face

Repo makeup

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.safetensors53.8 GB · 100%

At a glance

License: apache-2.0
Model type: qwen3_5_text
Access: Public
Created: Apr 11, 2026
Updated: Apr 22, 2026
SHA: 3a91ca03

Base models

Qwen/Qwen3.5-27B

Model card

From the Hugging Face model README

Ostrich 27B - Qwen 3.5 with Improved Answers in Certain Domains

Ostrich LLMs, bringing you "the knowledge that matters".

Health, nutrition, medicinal herbs
Fasting, faith, healing
Liberating technologies like bitcoin and nostr

AHA 2026 average score 73%

Per domain:

domain	match percent	matched/total
faith	84%	21/25
fasting	75%	65/87
health	77%	83/108
nutrition	61%	44/72
misinfo	57%	26/46
bitcoin	81%	50/62
alt-med	80%	45/56
herbs	83%	25/30
nostr	60%	27/45

Why: https://huggingface.co/blog/etemiz/building-a-beneficial-ai

Comparison of some answers between another of our fine tune and base model: https://sheet.zohopublic.com/sheet/published/um332e3d15f34bfe64605ad3c1b149c9f8ca4 These answers are not from this model but it is a similar work.

GSPO training made the thinking lengths shorter. I mainly targeted about 3000 letters (~1000 tokens) for thinking budget. If your Qwen 3.5 is endlessly reasoning, try this one.

Methods used for fine tuning:

CPT
SFT
GSPO

My last article: https://huggingface.co/blog/etemiz/from-robots-that-prey-to-robots-that-pray

Thanks @unslothai for providing amazing tools.