Create README.md

README.md

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+---
+license: apache-2.0
+base_model:
+- Qwen/Qwen3-32B
+tags:
+- '#aha'
+- '#health'
+- '#nutrition'
+- '#medicinalherbs'
+- '#fasting'
+- '#faith'
+- '#healing'
+- '#bitcoin'
+- '#nostr'
+---
+
+![Ostrich 32B](https://cdn-uploads.huggingface.co/production/uploads/65a488b5224f96d8cc3754fc/eLIx_6ZKB6qGKJHh_P3De.png)
+
+
+
+Ostrich 32B - bringing you "the knowledge that matters".
+
+- Health, nutrition, medicinal herbs
+- Fasting, faith, healing
+- Liberating technologies like bitcoin and nostr
+
+This is a similar project to my [Gemma 3 fine tuning](https://huggingface.co/blog/etemiz/fine-tuning-gemma-3-for-human-alignment), but here Qwen3 is the base model. There is a difference in the loop. For Gemma3 I was training in 4 bit, merging loras to the 16 bit model, taking gguf, measuring progress. For Qwen3 I saved in 4 bit, measured in 4 bit bitsandbytes and only worked with 16 bit models for merging using MergeKit.  
+
+Gemma 3 was resisting against faith and fasting domains. This one was happy to learn about those but still resisted in other domains. I will fine tune more and publish more models with proper AHA scores. For now this is a temporary release.  
+
+Purpose of the work: [Curation is All You Need](https://huggingface.co/blog/etemiz/curation-is-all-you-need).
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+Check out [the original Ostrich](https://huggingface.co/some1nostr/Ostrich-70B).
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+Project sponsored by [PickaBrain](https://pickabrain.ai).
+
+If you want the better human alignment you can talk to [Kooby](https://pickabrain.ai/ko).