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@@ -64,22 +64,22 @@ images = pipe(
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  </details>
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- <table>
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  <tbody>
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  <tr>
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- <td align="center"><img src="https://huggingface.co/sayakpaul/lower-rank-flux-lora/resolve/main/images/collage_0.png" alt="Image 1"></td>
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  <td align="center">Yorkshire Terrier with smile, How2Draw</td>
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  </tr>
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  <tr>
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- <td align="center"><img src="https://huggingface.co/sayakpaul/lower-rank-flux-lora/resolve/main/images/collage_1.png" alt="Image 2"></td>
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  <td align="center">a dolphin, How2Draw</td>
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  </tr>
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  <tr>
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- <td align="center"><img src="https://huggingface.co/sayakpaul/lower-rank-flux-lora/resolve/main/images/collage_2.png" alt="Image 3"></td>
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  <td align="center">an owl, How3Draw</td>
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  </tr>
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  <tr>
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- <td align="center"><img src="https://huggingface.co/sayakpaul/lower-rank-flux-lora/resolve/main/images/collage_3.png" alt="Image 4"></td>
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  <td align="center">
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  A silhouette of a girl performing a ballet pose, with elegant lines to suggest grace and movement.
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  The background can include simple outlines of ballet shoes and a music note.
@@ -99,7 +99,8 @@ Code: [`low_rank_lora.py`](https://huggingface.co/sayakpaul/lower-rank-flux-lor
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  ## SVD
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- ### Results
 
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  ![image.png](https://huggingface.co/sayakpaul/lower-rank-flux-lora/resolve/main/images/How2Draw-V2_000002800_svd_collage_0.png)
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@@ -109,10 +110,15 @@ Code: [`low_rank_lora.py`](https://huggingface.co/sayakpaul/lower-rank-flux-lor
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  ![image.png](https://huggingface.co/sayakpaul/lower-rank-flux-lora/resolve/main/images/How2Draw-V2_000002800_svd_collage_3.png)
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  ### Randomized SVD
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  Full SVD can be time-consuming. Truncated SVD is useful very large sparse matrices. We can use randomized SVD for none-to-negligible loss in quality but significantly faster speed.
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  ![image.png](https://huggingface.co/sayakpaul/lower-rank-flux-lora/resolve/main/images/How2Draw-V2_000002800_rand_svd_collage_0.png)
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  ![image.png](https://huggingface.co/sayakpaul/lower-rank-flux-lora/resolve/main/images/How2Draw-V2_000002800_rand_svd_collage_1.png)
@@ -120,10 +126,18 @@ Full SVD can be time-consuming. Truncated SVD is useful very large sparse matric
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  ![image.png](https://huggingface.co/sayakpaul/lower-rank-flux-lora/resolve/main/images/How2Draw-V2_000002800_rand_svd_collage_2.png)
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  ![image.png](https://huggingface.co/sayakpaul/lower-rank-flux-lora/resolve/main/images/How2Draw-V2_000002800_rand_svd_collage_3.png)
 
 
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  Code: [`svd_low_rank_lora.py`](https://huggingface.co/sayakpaul/lower-rank-flux-lora/blob/main/svd_low_rank_lora.py)
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  ### Tune the knobs in SVD
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  - `new_rank` as always
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- - `niter` when using randomized SVD
 
 
 
 
 
 
 
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  </details>
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+ <table border=1>
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  <tbody>
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  <tr>
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+ <td align="center"><img src="https://huggingface.co/sayakpaul/lower-rank-flux-lora/resolve/main/images/collage_0.png" width=300 alt="Image 1"></td>
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  <td align="center">Yorkshire Terrier with smile, How2Draw</td>
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  </tr>
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  <tr>
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+ <td align="center"><img src="https://huggingface.co/sayakpaul/lower-rank-flux-lora/resolve/main/images/collage_1.png" width=300 alt="Image 2"></td>
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  <td align="center">a dolphin, How2Draw</td>
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  </tr>
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  <tr>
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+ <td align="center"><img src="https://huggingface.co/sayakpaul/lower-rank-flux-lora/resolve/main/images/collage_2.png" width=300 alt="Image 3"></td>
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  <td align="center">an owl, How3Draw</td>
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  </tr>
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  <tr>
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+ <td align="center"><img src="https://huggingface.co/sayakpaul/lower-rank-flux-lora/resolve/main/images/collage_3.png" width=300 alt="Image 4"></td>
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  <td align="center">
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  A silhouette of a girl performing a ballet pose, with elegant lines to suggest grace and movement.
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  The background can include simple outlines of ballet shoes and a music note.
 
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  ## SVD
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+ <details>
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+ <summary><h3>Results</h3></summary>
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  ![image.png](https://huggingface.co/sayakpaul/lower-rank-flux-lora/resolve/main/images/How2Draw-V2_000002800_svd_collage_0.png)
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  ![image.png](https://huggingface.co/sayakpaul/lower-rank-flux-lora/resolve/main/images/How2Draw-V2_000002800_svd_collage_3.png)
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+ </details>
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+
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  ### Randomized SVD
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  Full SVD can be time-consuming. Truncated SVD is useful very large sparse matrices. We can use randomized SVD for none-to-negligible loss in quality but significantly faster speed.
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+ <details>
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+ <summary>Resukts</summary>
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+
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  ![image.png](https://huggingface.co/sayakpaul/lower-rank-flux-lora/resolve/main/images/How2Draw-V2_000002800_rand_svd_collage_0.png)
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  ![image.png](https://huggingface.co/sayakpaul/lower-rank-flux-lora/resolve/main/images/How2Draw-V2_000002800_rand_svd_collage_1.png)
 
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  ![image.png](https://huggingface.co/sayakpaul/lower-rank-flux-lora/resolve/main/images/How2Draw-V2_000002800_rand_svd_collage_2.png)
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  ![image.png](https://huggingface.co/sayakpaul/lower-rank-flux-lora/resolve/main/images/How2Draw-V2_000002800_rand_svd_collage_3.png)
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+
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+ </details>
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  Code: [`svd_low_rank_lora.py`](https://huggingface.co/sayakpaul/lower-rank-flux-lora/blob/main/svd_low_rank_lora.py)
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  ### Tune the knobs in SVD
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  - `new_rank` as always
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+ - `niter` when using randomized SVD
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+
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+ ## Reduced checkpoints
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+
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+ * Randomized SVD: [How2Draw-V2_000002800_rand_svd.safetensors](./How2Draw-V2_000002800_rand_svd.safetensors)
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+ * Full SVD: [How2Draw-V2_000002800_svd.safetensors](./How2Draw-V2_000002800_svd.safetensors)
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+ * Random projections: [How2Draw-V2_000002800_reduced.safetensors](./How2Draw-V2_000002800_reduced.safetensors)