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Park JuHoon

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reacted to danielhanchen's post with πŸ”₯ about 21 hours ago
You can now fine-tune embedding models in our free Unsloth notebook! πŸ€— Fine-tuning embedding models improves retrieval & RAG by aligning vectors to your domain-specific notion of similarity, improving search, clustering, and recommendations on your data. ⭐ Blog + Notebooks: https://unsloth.ai/docs/new/embedding-finetuning Unsloth trains embedding models 1.8-3.3x faster with 20% less VRAM, 2x longer context & no accuracy loss vs. FA2 setups. We'd like to thank Hugging Face and Unsloth contributor: electroglyph for making this possible!
reacted to danielhanchen's post with πŸ€— about 21 hours ago
You can now fine-tune embedding models in our free Unsloth notebook! πŸ€— Fine-tuning embedding models improves retrieval & RAG by aligning vectors to your domain-specific notion of similarity, improving search, clustering, and recommendations on your data. ⭐ Blog + Notebooks: https://unsloth.ai/docs/new/embedding-finetuning Unsloth trains embedding models 1.8-3.3x faster with 20% less VRAM, 2x longer context & no accuracy loss vs. FA2 setups. We'd like to thank Hugging Face and Unsloth contributor: electroglyph for making this possible!
reacted to danielhanchen's post with ❀️ about 21 hours ago
You can now fine-tune embedding models in our free Unsloth notebook! πŸ€— Fine-tuning embedding models improves retrieval & RAG by aligning vectors to your domain-specific notion of similarity, improving search, clustering, and recommendations on your data. ⭐ Blog + Notebooks: https://unsloth.ai/docs/new/embedding-finetuning Unsloth trains embedding models 1.8-3.3x faster with 20% less VRAM, 2x longer context & no accuracy loss vs. FA2 setups. We'd like to thank Hugging Face and Unsloth contributor: electroglyph for making this possible!
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