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README.md
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@@ -102,7 +102,7 @@ In general, the way to think about these (non-orthogonal) "multiplicative-LoRAs"
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So instead of having just a single vector that we add (and in essence adding a `'.bias'` weight to create an [affine transformation](https://en.wikipedia.org/wiki/Affine_transformation)), we now have many different control vectors that can be added (stored in `lora_B`), based on how well they match another set of "direction detection vectors" (stored in `lora_A`).
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**NOTE**: The [LoRA+](https://arxiv.org/abs/2402.12354) paper uses a similar way of viewing the purpose of `lora_A` and `lora_B
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/65995c45539c808e84c38bf1/vZ2Gys3huKAWIVe0wz2-q.png)
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So instead of having just a single vector that we add (and in essence adding a `'.bias'` weight to create an [affine transformation](https://en.wikipedia.org/wiki/Affine_transformation)), we now have many different control vectors that can be added (stored in `lora_B`), based on how well they match another set of "direction detection vectors" (stored in `lora_A`).
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**NOTE**: The [LoRA+](https://arxiv.org/abs/2402.12354) paper uses a similar way of viewing the purpose of `lora_A` and `lora_B`:
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/65995c45539c808e84c38bf1/vZ2Gys3huKAWIVe0wz2-q.png)
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