Update README.md
Browse files
README.md
CHANGED
@@ -21,9 +21,8 @@ how you can load this into a diffusers-based notebook like [Doohickey](https://g
|
|
21 |
from huggingface_hub import hf_hub_download
|
22 |
|
23 |
stable_inversion = "user/my-stable-inversion" #@param {type:"string"}
|
24 |
-
|
25 |
-
|
26 |
-
text_encoder.text_model.embeddings.token_embedding.weight = torch.load(g)
|
27 |
```
|
28 |
|
29 |
it was trained on 1024 images matching the 'genshin_impact' tag on safebooru, epochs 1 and 2 had the model being fed the full captions, epoch 3 had 50% of the tags in the caption, and epoch 4 had 25% of the tags in the caption. Learning rate was 1e-3 and the loss curve looked like this ![](https://pbs.twimg.com/media/FdsdivkWIBQYmZd?format=jpg&name=small)
|
|
|
21 |
from huggingface_hub import hf_hub_download
|
22 |
|
23 |
stable_inversion = "user/my-stable-inversion" #@param {type:"string"}
|
24 |
+
inversion_path = hf_hub_download(repo_id=stable_inversion, filename="token_embeddings.pt")
|
25 |
+
text_encoder.text_model.embeddings.token_embedding.weight = torch.load(inversion_path)
|
|
|
26 |
```
|
27 |
|
28 |
it was trained on 1024 images matching the 'genshin_impact' tag on safebooru, epochs 1 and 2 had the model being fed the full captions, epoch 3 had 50% of the tags in the caption, and epoch 4 had 25% of the tags in the caption. Learning rate was 1e-3 and the loss curve looked like this ![](https://pbs.twimg.com/media/FdsdivkWIBQYmZd?format=jpg&name=small)
|