Hugging Face's logo

Datasets:
codeShare
/
lora-training-data

Dataset card Files Community
1
codeShare commited on
Commit
48d2b52
·
verified ·
1 Parent(s): 147638d

Upload lora_merge.ipynb

Browse files
Files changed (1) hide show
  1. lora_merge.ipynb +724 -0
lora_merge.ipynb ADDED
@@ -0,0 +1,724 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "nbformat": 4,
3
+ "nbformat_minor": 0,
4
+ "metadata": {
5
+ "colab": {
6
+ "provenance": []
7
+ },
8
+ "kernelspec": {
9
+ "name": "python3",
10
+ "display_name": "Python 3"
11
+ },
12
+ "language_info": {
13
+ "name": "python"
14
+ }
15
+ },
16
+ "cells": [
17
+ {
18
+ "cell_type": "markdown",
19
+ "source": [
20
+ "# Cast civitai trained LoRa in torch.bfloat16 to Tensor Art Compatible torch.float16 dtype\n",
21
+ "\n",
22
+ "Created by Adcom: https://tensor.art/u/743241123023077878"
23
+ ],
24
+ "metadata": {
25
+ "id": "YDCnQpDdqDe4"
26
+ }
27
+ },
28
+ {
29
+ "cell_type": "code",
30
+ "source": [
31
+ "#initialize\n",
32
+ "import torch\n",
33
+ "from safetensors.torch import load_file\n",
34
+ "from google.colab import drive\n",
35
+ "drive.mount('/content/drive')"
36
+ ],
37
+ "metadata": {
38
+ "id": "1oxeJYHRqxQC",
39
+ "outputId": "5397ceb1-cd98-4477-f472-d766beac79fb",
40
+ "colab": {
41
+ "base_uri": "https://localhost:8080/"
42
+ }
43
+ },
44
+ "execution_count": 1,
45
+ "outputs": [
46
+ {
47
+ "output_type": "stream",
48
+ "name": "stdout",
49
+ "text": [
50
+ "Mounted at /content/drive\n"
51
+ ]
52
+ }
53
+ ]
54
+ },
55
+ {
56
+ "cell_type": "code",
57
+ "source": [
58
+ "cgi = load_file('/content/drive/MyDrive/Saved from Chrome/cgi_style.safetensors')"
59
+ ],
60
+ "metadata": {
61
+ "id": "JuGDCX5272Bh"
62
+ },
63
+ "execution_count": 10,
64
+ "outputs": []
65
+ },
66
+ {
67
+ "cell_type": "code",
68
+ "source": [
69
+ "cgi = load_file('/content/drive/MyDrive/Saved from Chrome/cgi_style.safetensors')\n",
70
+ "iris = load_file('/content/drive/MyDrive/Saved from Chrome/proud_iris.safetensors')\n",
71
+ "nudism = load_file('/content/drive/MyDrive/Saved from Chrome/nudism.safetensors')"
72
+ ],
73
+ "metadata": {
74
+ "id": "FftDdBRG7su6"
75
+ },
76
+ "execution_count": 107,
77
+ "outputs": []
78
+ },
79
+ {
80
+ "cell_type": "code",
81
+ "source": [
82
+ "for key in cgi:\n",
83
+ " cgi[f'{key}'] = cgi[f'{key}'].to(dtype=torch.float16)\n",
84
+ " iris[f'{key}'] = iris[f'{key}'].to(dtype=torch.float16)\n",
85
+ " nudism[f'{key}'] = nudism[f'{key}'].to(dtype=torch.float16)"
86
+ ],
87
+ "metadata": {
88
+ "id": "RII9SEqh8KH2"
89
+ },
90
+ "execution_count": 108,
91
+ "outputs": []
92
+ },
93
+ {
94
+ "cell_type": "code",
95
+ "source": [
96
+ "import torch\n",
97
+ "import torch.nn as nn\n",
98
+ "#define metric for similarity\n",
99
+ "tgt_dim = torch.Size([64, 3072])\n",
100
+ "cos0 = nn.CosineSimilarity(dim=1)\n",
101
+ "cos = nn.CosineSimilarity(dim=1)\n",
102
+ "\n",
103
+ "\n",
104
+ "def sim(tgt , ref ,key):\n",
105
+ " return torch.sum(torch.abs(cos(tgt, ref[f'{key}']))) + torch.sum(torch.abs(cos0(tgt, ref[f'{key}'])))\n",
106
+ "#-----#\n",
107
+ "\n",
108
+ "from torch import linalg as LA\n",
109
+ "def rand_search(A , B , key , iters):\n",
110
+ " tgt_norm = (LA.matrix_norm(A[f'{key}']) + LA.matrix_norm(B[f'{key}']))/2\n",
111
+ " tgt_avg = (A[f'{key}'] + B[f'{key}'])/2\n",
112
+ "\n",
113
+ " max_sim = (sim(tgt_avg , A , key) + sim(tgt_avg , B , key))\n",
114
+ " cand = tgt_avg\n",
115
+ "\n",
116
+ " for iter in range(iters):\n",
117
+ " rand = torch.ones(tgt_dim)*(-0.5) + torch.rand(tgt_dim)\n",
118
+ " rand = rand * (tgt_norm/LA.matrix_norm(rand))\n",
119
+ " #rand = (rand + tgt_avg)/2\n",
120
+ " #rand = rand * (tgt_norm/LA.matrix_norm(rand))\n",
121
+ "\n",
122
+ " tmp = sim(rand,A, key) + sim(rand , B, key)\n",
123
+ " if (tmp > max_sim):\n",
124
+ " max_sim = tmp\n",
125
+ " cand = rand\n",
126
+ " print('found!')\n",
127
+ " break\n",
128
+ " #------#\n",
129
+ " print('returning')\n",
130
+ " return cand , max_sim\n",
131
+ "#-----#"
132
+ ],
133
+ "metadata": {
134
+ "id": "hJL6QEclHdHn"
135
+ },
136
+ "execution_count": 104,
137
+ "outputs": []
138
+ },
139
+ {
140
+ "cell_type": "code",
141
+ "source": [
142
+ "cand , max_sim = rand_search(cgi , iris , 'lora_unet_double_blocks_0_img_attn_proj.lora_down.weight' , 1000)\n",
143
+ "print(sim(cand , iris , key))\n",
144
+ "print(sim(cand , cgi , key))"
145
+ ],
146
+ "metadata": {
147
+ "id": "ckyBSQi5Ll4F",
148
+ "outputId": "341f7192-083d-4423-f61f-4f49d5756e79",
149
+ "colab": {
150
+ "base_uri": "https://localhost:8080/"
151
+ }
152
+ },
153
+ "execution_count": 106,
154
+ "outputs": [
155
+ {
156
+ "output_type": "stream",
157
+ "name": "stdout",
158
+ "text": [
159
+ "returning\n",
160
+ "tensor(91.1875, dtype=torch.float16)\n",
161
+ "tensor(90.2500, dtype=torch.float16)\n"
162
+ ]
163
+ }
164
+ ]
165
+ },
166
+ {
167
+ "cell_type": "code",
168
+ "source": [
169
+ "from safetensors.torch import load_file , save_file\n",
170
+ "\n",
171
+ "merge = load_file('/content/drive/MyDrive/Saved from Chrome/cgi_style.safetensors')\n",
172
+ "for key in cgi:\n",
173
+ " if cgi[f'{key}'].shape == torch.Size([]): continue\n",
174
+ " merge[f'{key}'] = (cgi[f'{key}'] + iris[f'{key}'])/2\n",
175
+ "\n",
176
+ "%cd /content/\n",
177
+ "save_file(merge , 'cgi_iris_1_1_1_merge.safetensors')"
178
+ ],
179
+ "metadata": {
180
+ "id": "9L_g5Zp9Du2E",
181
+ "outputId": "38661765-461a-42c3-8480-38fe7f1abe3e",
182
+ "colab": {
183
+ "base_uri": "https://localhost:8080/"
184
+ }
185
+ },
186
+ "execution_count": 113,
187
+ "outputs": [
188
+ {
189
+ "output_type": "stream",
190
+ "name": "stdout",
191
+ "text": [
192
+ "/content\n"
193
+ ]
194
+ }
195
+ ]
196
+ },
197
+ {
198
+ "cell_type": "code",
199
+ "source": [
200
+ "tgt_dim = torch.Size([64, 3072])\n",
201
+ "cosa = nn.CosineSimilarity(dim=0)\n",
202
+ "cos_dim1 = nn.CosineSimilarity(dim=1)\n",
203
+ "\n",
204
+ "for key in cgi:\n",
205
+ " if not cgi[f'{key}'].shape == torch.Size([64, 3072]): continue\n",
206
+ " print(f'{key} : ')\n",
207
+ " print(torch.sum(torch.abs(cos_dim1(cgi[f'{key}'] , iris[f'{key}']))))"
208
+ ],
209
+ "metadata": {
210
+ "id": "VFNw0Nck8V6Q",
211
+ "outputId": "e48bab98-18f7-43bb-d1cf-89f3e00f7ccf",
212
+ "colab": {
213
+ "base_uri": "https://localhost:8080/"
214
+ }
215
+ },
216
+ "execution_count": 39,
217
+ "outputs": [
218
+ {
219
+ "output_type": "stream",
220
+ "name": "stdout",
221
+ "text": [
222
+ "lora_unet_double_blocks_0_img_attn_proj.lora_down.weight : \n",
223
+ "tensor(1.6982, dtype=torch.float16)\n",
224
+ "lora_unet_double_blocks_0_img_attn_qkv.lora_down.weight : \n",
225
+ "tensor(1.8145, dtype=torch.float16)\n",
226
+ "lora_unet_double_blocks_0_img_mlp_0.lora_down.weight : \n",
227
+ "tensor(1.6309, dtype=torch.float16)\n",
228
+ "lora_unet_double_blocks_0_img_mod_lin.lora_down.weight : \n",
229
+ "tensor(2.6211, dtype=torch.float16)\n",
230
+ "lora_unet_double_blocks_0_txt_attn_proj.lora_down.weight : \n",
231
+ "tensor(2.3203, dtype=torch.float16)\n",
232
+ "lora_unet_double_blocks_0_txt_attn_qkv.lora_down.weight : \n",
233
+ "tensor(2.3027, dtype=torch.float16)\n",
234
+ "lora_unet_double_blocks_0_txt_mlp_0.lora_down.weight : \n",
235
+ "tensor(2.5898, dtype=torch.float16)\n",
236
+ "lora_unet_double_blocks_0_txt_mod_lin.lora_down.weight : \n",
237
+ "tensor(2.7402, dtype=torch.float16)\n",
238
+ "lora_unet_double_blocks_10_img_attn_proj.lora_down.weight : \n",
239
+ "tensor(2.0410, dtype=torch.float16)\n",
240
+ "lora_unet_double_blocks_10_img_attn_qkv.lora_down.weight : \n",
241
+ "tensor(1.3350, dtype=torch.float16)\n",
242
+ "lora_unet_double_blocks_10_img_mlp_0.lora_down.weight : \n",
243
+ "tensor(2.0020, dtype=torch.float16)\n",
244
+ "lora_unet_double_blocks_10_img_mod_lin.lora_down.weight : \n",
245
+ "tensor(2.6562, dtype=torch.float16)\n",
246
+ "lora_unet_double_blocks_10_txt_attn_proj.lora_down.weight : \n",
247
+ "tensor(1.1816, dtype=torch.float16)\n",
248
+ "lora_unet_double_blocks_10_txt_attn_qkv.lora_down.weight : \n",
249
+ "tensor(1.1348, dtype=torch.float16)\n",
250
+ "lora_unet_double_blocks_10_txt_mlp_0.lora_down.weight : \n",
251
+ "tensor(3.0156, dtype=torch.float16)\n",
252
+ "lora_unet_double_blocks_10_txt_mod_lin.lora_down.weight : \n",
253
+ "tensor(1.4746, dtype=torch.float16)\n",
254
+ "lora_unet_double_blocks_11_img_attn_proj.lora_down.weight : \n",
255
+ "tensor(1.8359, dtype=torch.float16)\n",
256
+ "lora_unet_double_blocks_11_img_attn_qkv.lora_down.weight : \n",
257
+ "tensor(1.5312, dtype=torch.float16)\n",
258
+ "lora_unet_double_blocks_11_img_mlp_0.lora_down.weight : \n",
259
+ "tensor(2.1465, dtype=torch.float16)\n",
260
+ "lora_unet_double_blocks_11_img_mod_lin.lora_down.weight : \n",
261
+ "tensor(3.9277, dtype=torch.float16)\n",
262
+ "lora_unet_double_blocks_11_txt_attn_proj.lora_down.weight : \n",
263
+ "tensor(1.7246, dtype=torch.float16)\n",
264
+ "lora_unet_double_blocks_11_txt_attn_qkv.lora_down.weight : \n",
265
+ "tensor(1.8594, dtype=torch.float16)\n",
266
+ "lora_unet_double_blocks_11_txt_mlp_0.lora_down.weight : \n",
267
+ "tensor(3.6465, dtype=torch.float16)\n",
268
+ "lora_unet_double_blocks_11_txt_mod_lin.lora_down.weight : \n",
269
+ "tensor(2.6152, dtype=torch.float16)\n",
270
+ "lora_unet_double_blocks_12_img_attn_proj.lora_down.weight : \n",
271
+ "tensor(1.7295, dtype=torch.float16)\n",
272
+ "lora_unet_double_blocks_12_img_attn_qkv.lora_down.weight : \n",
273
+ "tensor(1.4795, dtype=torch.float16)\n",
274
+ "lora_unet_double_blocks_12_img_mlp_0.lora_down.weight : \n",
275
+ "tensor(3.4043, dtype=torch.float16)\n",
276
+ "lora_unet_double_blocks_12_img_mod_lin.lora_down.weight : \n",
277
+ "tensor(2.0137, dtype=torch.float16)\n",
278
+ "lora_unet_double_blocks_12_txt_attn_proj.lora_down.weight : \n",
279
+ "tensor(1.4375, dtype=torch.float16)\n",
280
+ "lora_unet_double_blocks_12_txt_attn_qkv.lora_down.weight : \n",
281
+ "tensor(1.8994, dtype=torch.float16)\n",
282
+ "lora_unet_double_blocks_12_txt_mlp_0.lora_down.weight : \n",
283
+ "tensor(2.1152, dtype=torch.float16)\n",
284
+ "lora_unet_double_blocks_12_txt_mod_lin.lora_down.weight : \n",
285
+ "tensor(1.2744, dtype=torch.float16)\n",
286
+ "lora_unet_double_blocks_13_img_attn_proj.lora_down.weight : \n",
287
+ "tensor(3.0742, dtype=torch.float16)\n",
288
+ "lora_unet_double_blocks_13_img_attn_qkv.lora_down.weight : \n",
289
+ "tensor(1.4980, dtype=torch.float16)\n",
290
+ "lora_unet_double_blocks_13_img_mlp_0.lora_down.weight : \n",
291
+ "tensor(1.9609, dtype=torch.float16)\n",
292
+ "lora_unet_double_blocks_13_img_mod_lin.lora_down.weight : \n",
293
+ "tensor(2.6133, dtype=torch.float16)\n",
294
+ "lora_unet_double_blocks_13_txt_attn_proj.lora_down.weight : \n",
295
+ "tensor(1.6904, dtype=torch.float16)\n",
296
+ "lora_unet_double_blocks_13_txt_attn_qkv.lora_down.weight : \n",
297
+ "tensor(2.1680, dtype=torch.float16)\n",
298
+ "lora_unet_double_blocks_13_txt_mlp_0.lora_down.weight : \n",
299
+ "tensor(2.8574, dtype=torch.float16)\n",
300
+ "lora_unet_double_blocks_13_txt_mod_lin.lora_down.weight : \n",
301
+ "tensor(1.9053, dtype=torch.float16)\n",
302
+ "lora_unet_double_blocks_14_img_attn_proj.lora_down.weight : \n",
303
+ "tensor(1.8135, dtype=torch.float16)\n",
304
+ "lora_unet_double_blocks_14_img_attn_qkv.lora_down.weight : \n",
305
+ "tensor(1.4033, dtype=torch.float16)\n",
306
+ "lora_unet_double_blocks_14_img_mlp_0.lora_down.weight : \n",
307
+ "tensor(1.5547, dtype=torch.float16)\n",
308
+ "lora_unet_double_blocks_14_img_mod_lin.lora_down.weight : \n",
309
+ "tensor(2.8906, dtype=torch.float16)\n",
310
+ "lora_unet_double_blocks_14_txt_attn_proj.lora_down.weight : \n",
311
+ "tensor(1.1328, dtype=torch.float16)\n",
312
+ "lora_unet_double_blocks_14_txt_attn_qkv.lora_down.weight : \n",
313
+ "tensor(1.3701, dtype=torch.float16)\n",
314
+ "lora_unet_double_blocks_14_txt_mlp_0.lora_down.weight : \n",
315
+ "tensor(3.3145, dtype=torch.float16)\n",
316
+ "lora_unet_double_blocks_14_txt_mod_lin.lora_down.weight : \n",
317
+ "tensor(1.2031, dtype=torch.float16)\n",
318
+ "lora_unet_double_blocks_15_img_attn_proj.lora_down.weight : \n",
319
+ "tensor(1.5137, dtype=torch.float16)\n",
320
+ "lora_unet_double_blocks_15_img_attn_qkv.lora_down.weight : \n",
321
+ "tensor(1.3809, dtype=torch.float16)\n",
322
+ "lora_unet_double_blocks_15_img_mlp_0.lora_down.weight : \n",
323
+ "tensor(1.4834, dtype=torch.float16)\n",
324
+ "lora_unet_double_blocks_15_img_mod_lin.lora_down.weight : \n",
325
+ "tensor(1.6465, dtype=torch.float16)\n",
326
+ "lora_unet_double_blocks_15_txt_attn_proj.lora_down.weight : \n",
327
+ "tensor(1.7256, dtype=torch.float16)\n",
328
+ "lora_unet_double_blocks_15_txt_attn_qkv.lora_down.weight : \n",
329
+ "tensor(2.8672, dtype=torch.float16)\n",
330
+ "lora_unet_double_blocks_15_txt_mlp_0.lora_down.weight : \n",
331
+ "tensor(2.1953, dtype=torch.float16)\n",
332
+ "lora_unet_double_blocks_15_txt_mod_lin.lora_down.weight : \n",
333
+ "tensor(0.9858, dtype=torch.float16)\n",
334
+ "lora_unet_double_blocks_16_img_attn_proj.lora_down.weight : \n",
335
+ "tensor(1.5703, dtype=torch.float16)\n",
336
+ "lora_unet_double_blocks_16_img_attn_qkv.lora_down.weight : \n",
337
+ "tensor(1.4648, dtype=torch.float16)\n",
338
+ "lora_unet_double_blocks_16_img_mlp_0.lora_down.weight : \n",
339
+ "tensor(1.5537, dtype=torch.float16)\n",
340
+ "lora_unet_double_blocks_16_img_mod_lin.lora_down.weight : \n",
341
+ "tensor(2.6133, dtype=torch.float16)\n",
342
+ "lora_unet_double_blocks_16_txt_attn_proj.lora_down.weight : \n",
343
+ "tensor(2.2559, dtype=torch.float16)\n",
344
+ "lora_unet_double_blocks_16_txt_attn_qkv.lora_down.weight : \n",
345
+ "tensor(1.9365, dtype=torch.float16)\n",
346
+ "lora_unet_double_blocks_16_txt_mlp_0.lora_down.weight : \n",
347
+ "tensor(2.7891, dtype=torch.float16)\n",
348
+ "lora_unet_double_blocks_16_txt_mod_lin.lora_down.weight : \n",
349
+ "tensor(1.3174, dtype=torch.float16)\n",
350
+ "lora_unet_double_blocks_17_img_attn_proj.lora_down.weight : \n",
351
+ "tensor(2.4609, dtype=torch.float16)\n",
352
+ "lora_unet_double_blocks_17_img_attn_qkv.lora_down.weight : \n",
353
+ "tensor(1.6240, dtype=torch.float16)\n",
354
+ "lora_unet_double_blocks_17_img_mlp_0.lora_down.weight : \n",
355
+ "tensor(3.1406, dtype=torch.float16)\n",
356
+ "lora_unet_double_blocks_17_img_mod_lin.lora_down.weight : \n",
357
+ "tensor(2.1055, dtype=torch.float16)\n",
358
+ "lora_unet_double_blocks_17_txt_attn_proj.lora_down.weight : \n",
359
+ "tensor(1.7480, dtype=torch.float16)\n",
360
+ "lora_unet_double_blocks_17_txt_attn_qkv.lora_down.weight : \n",
361
+ "tensor(1.6436, dtype=torch.float16)\n",
362
+ "lora_unet_double_blocks_17_txt_mlp_0.lora_down.weight : \n",
363
+ "tensor(1.9688, dtype=torch.float16)\n",
364
+ "lora_unet_double_blocks_17_txt_mod_lin.lora_down.weight : \n",
365
+ "tensor(1.8184, dtype=torch.float16)\n",
366
+ "lora_unet_double_blocks_18_img_attn_proj.lora_down.weight : \n",
367
+ "tensor(2.3887, dtype=torch.float16)\n",
368
+ "lora_unet_double_blocks_18_img_attn_qkv.lora_down.weight : \n",
369
+ "tensor(1.6738, dtype=torch.float16)\n",
370
+ "lora_unet_double_blocks_18_img_mlp_0.lora_down.weight : \n",
371
+ "tensor(3.7500, dtype=torch.float16)\n",
372
+ "lora_unet_double_blocks_18_img_mod_lin.lora_down.weight : \n",
373
+ "tensor(2.7285, dtype=torch.float16)\n",
374
+ "lora_unet_double_blocks_18_txt_attn_proj.lora_down.weight : \n",
375
+ "tensor(2.0410, dtype=torch.float16)\n",
376
+ "lora_unet_double_blocks_18_txt_attn_qkv.lora_down.weight : \n",
377
+ "tensor(2.0586, dtype=torch.float16)\n",
378
+ "lora_unet_double_blocks_18_txt_mlp_0.lora_down.weight : \n",
379
+ "tensor(2.0801, dtype=torch.float16)\n",
380
+ "lora_unet_double_blocks_18_txt_mod_lin.lora_down.weight : \n",
381
+ "tensor(1.5684, dtype=torch.float16)\n",
382
+ "lora_unet_double_blocks_1_img_attn_proj.lora_down.weight : \n",
383
+ "tensor(4.9844, dtype=torch.float16)\n",
384
+ "lora_unet_double_blocks_1_img_attn_qkv.lora_down.weight : \n",
385
+ "tensor(1.8613, dtype=torch.float16)\n",
386
+ "lora_unet_double_blocks_1_img_mlp_0.lora_down.weight : \n",
387
+ "tensor(2.2266, dtype=torch.float16)\n",
388
+ "lora_unet_double_blocks_1_img_mod_lin.lora_down.weight : \n",
389
+ "tensor(2.8164, dtype=torch.float16)\n",
390
+ "lora_unet_double_blocks_1_txt_attn_proj.lora_down.weight : \n",
391
+ "tensor(1.7500, dtype=torch.float16)\n",
392
+ "lora_unet_double_blocks_1_txt_attn_qkv.lora_down.weight : \n",
393
+ "tensor(2.3105, dtype=torch.float16)\n",
394
+ "lora_unet_double_blocks_1_txt_mlp_0.lora_down.weight : \n",
395
+ "tensor(1.9639, dtype=torch.float16)\n",
396
+ "lora_unet_double_blocks_1_txt_mod_lin.lora_down.weight : \n",
397
+ "tensor(2.6504, dtype=torch.float16)\n",
398
+ "lora_unet_double_blocks_2_img_attn_proj.lora_down.weight : \n",
399
+ "tensor(4.6367, dtype=torch.float16)\n",
400
+ "lora_unet_double_blocks_2_img_attn_qkv.lora_down.weight : \n",
401
+ "tensor(1.7988, dtype=torch.float16)\n",
402
+ "lora_unet_double_blocks_2_img_mlp_0.lora_down.weight : \n",
403
+ "tensor(4.6758, dtype=torch.float16)\n",
404
+ "lora_unet_double_blocks_2_img_mod_lin.lora_down.weight : \n",
405
+ "tensor(3.1445, dtype=torch.float16)\n",
406
+ "lora_unet_double_blocks_2_txt_attn_proj.lora_down.weight : \n",
407
+ "tensor(2.2285, dtype=torch.float16)\n",
408
+ "lora_unet_double_blocks_2_txt_attn_qkv.lora_down.weight : \n",
409
+ "tensor(1.4990, dtype=torch.float16)\n",
410
+ "lora_unet_double_blocks_2_txt_mlp_0.lora_down.weight : \n",
411
+ "tensor(2.3984, dtype=torch.float16)\n",
412
+ "lora_unet_double_blocks_2_txt_mod_lin.lora_down.weight : \n",
413
+ "tensor(1.4443, dtype=torch.float16)\n",
414
+ "lora_unet_double_blocks_3_img_attn_proj.lora_down.weight : \n",
415
+ "tensor(3.6855, dtype=torch.float16)\n",
416
+ "lora_unet_double_blocks_3_img_attn_qkv.lora_down.weight : \n",
417
+ "tensor(1.9971, dtype=torch.float16)\n",
418
+ "lora_unet_double_blocks_3_img_mlp_0.lora_down.weight : \n",
419
+ "tensor(3.3301, dtype=torch.float16)\n",
420
+ "lora_unet_double_blocks_3_img_mod_lin.lora_down.weight : \n",
421
+ "tensor(2.3379, dtype=torch.float16)\n",
422
+ "lora_unet_double_blocks_3_txt_attn_proj.lora_down.weight : \n",
423
+ "tensor(2.0117, dtype=torch.float16)\n",
424
+ "lora_unet_double_blocks_3_txt_attn_qkv.lora_down.weight : \n",
425
+ "tensor(2.1621, dtype=torch.float16)\n",
426
+ "lora_unet_double_blocks_3_txt_mlp_0.lora_down.weight : \n",
427
+ "tensor(2.7676, dtype=torch.float16)\n",
428
+ "lora_unet_double_blocks_3_txt_mod_lin.lora_down.weight : \n",
429
+ "tensor(3.1895, dtype=torch.float16)\n",
430
+ "lora_unet_double_blocks_4_img_attn_proj.lora_down.weight : \n",
431
+ "tensor(2.3848, dtype=torch.float16)\n",
432
+ "lora_unet_double_blocks_4_img_attn_qkv.lora_down.weight : \n",
433
+ "tensor(1.7783, dtype=torch.float16)\n",
434
+ "lora_unet_double_blocks_4_img_mlp_0.lora_down.weight : \n",
435
+ "tensor(2.0234, dtype=torch.float16)\n",
436
+ "lora_unet_double_blocks_4_img_mod_lin.lora_down.weight : \n",
437
+ "tensor(1.9082, dtype=torch.float16)\n",
438
+ "lora_unet_double_blocks_4_txt_attn_proj.lora_down.weight : \n",
439
+ "tensor(1.7588, dtype=torch.float16)\n",
440
+ "lora_unet_double_blocks_4_txt_attn_qkv.lora_down.weight : \n",
441
+ "tensor(2.9902, dtype=torch.float16)\n",
442
+ "lora_unet_double_blocks_4_txt_mlp_0.lora_down.weight : \n",
443
+ "tensor(1.5859, dtype=torch.float16)\n",
444
+ "lora_unet_double_blocks_4_txt_mod_lin.lora_down.weight : \n",
445
+ "tensor(1.5654, dtype=torch.float16)\n",
446
+ "lora_unet_double_blocks_5_img_attn_proj.lora_down.weight : \n",
447
+ "tensor(2.7402, dtype=torch.float16)\n",
448
+ "lora_unet_double_blocks_5_img_attn_qkv.lora_down.weight : \n",
449
+ "tensor(1.6221, dtype=torch.float16)\n",
450
+ "lora_unet_double_blocks_5_img_mlp_0.lora_down.weight : \n",
451
+ "tensor(1.6318, dtype=torch.float16)\n",
452
+ "lora_unet_double_blocks_5_img_mod_lin.lora_down.weight : \n",
453
+ "tensor(1.7988, dtype=torch.float16)\n",
454
+ "lora_unet_double_blocks_5_txt_attn_proj.lora_down.weight : \n",
455
+ "tensor(1.1699, dtype=torch.float16)\n",
456
+ "lora_unet_double_blocks_5_txt_attn_qkv.lora_down.weight : \n",
457
+ "tensor(3.5566, dtype=torch.float16)\n",
458
+ "lora_unet_double_blocks_5_txt_mlp_0.lora_down.weight : \n",
459
+ "tensor(1.5791, dtype=torch.float16)\n",
460
+ "lora_unet_double_blocks_5_txt_mod_lin.lora_down.weight : \n",
461
+ "tensor(1.5547, dtype=torch.float16)\n",
462
+ "lora_unet_double_blocks_6_img_attn_proj.lora_down.weight : \n",
463
+ "tensor(1.7988, dtype=torch.float16)\n",
464
+ "lora_unet_double_blocks_6_img_attn_qkv.lora_down.weight : \n",
465
+ "tensor(1.4531, dtype=torch.float16)\n",
466
+ "lora_unet_double_blocks_6_img_mlp_0.lora_down.weight : \n",
467
+ "tensor(2.4141, dtype=torch.float16)\n",
468
+ "lora_unet_double_blocks_6_img_mod_lin.lora_down.weight : \n",
469
+ "tensor(6.0234, dtype=torch.float16)\n",
470
+ "lora_unet_double_blocks_6_txt_attn_proj.lora_down.weight : \n",
471
+ "tensor(1.0068, dtype=torch.float16)\n",
472
+ "lora_unet_double_blocks_6_txt_attn_qkv.lora_down.weight : \n",
473
+ "tensor(2.0098, dtype=torch.float16)\n",
474
+ "lora_unet_double_blocks_6_txt_mlp_0.lora_down.weight : \n",
475
+ "tensor(4.0312, dtype=torch.float16)\n",
476
+ "lora_unet_double_blocks_6_txt_mod_lin.lora_down.weight : \n",
477
+ "tensor(2.6309, dtype=torch.float16)\n",
478
+ "lora_unet_double_blocks_7_img_attn_proj.lora_down.weight : \n",
479
+ "tensor(1.4814, dtype=torch.float16)\n",
480
+ "lora_unet_double_blocks_7_img_attn_qkv.lora_down.weight : \n",
481
+ "tensor(1.4854, dtype=torch.float16)\n",
482
+ "lora_unet_double_blocks_7_img_mlp_0.lora_down.weight : \n",
483
+ "tensor(1.3877, dtype=torch.float16)\n",
484
+ "lora_unet_double_blocks_7_img_mod_lin.lora_down.weight : \n",
485
+ "tensor(2.3125, dtype=torch.float16)\n",
486
+ "lora_unet_double_blocks_7_txt_attn_proj.lora_down.weight : \n",
487
+ "tensor(3.4746, dtype=torch.float16)\n",
488
+ "lora_unet_double_blocks_7_txt_attn_qkv.lora_down.weight : \n",
489
+ "tensor(2.0430, dtype=torch.float16)\n",
490
+ "lora_unet_double_blocks_7_txt_mlp_0.lora_down.weight : \n",
491
+ "tensor(1.8018, dtype=torch.float16)\n",
492
+ "lora_unet_double_blocks_7_txt_mod_lin.lora_down.weight : \n",
493
+ "tensor(1.1709, dtype=torch.float16)\n",
494
+ "lora_unet_double_blocks_8_img_attn_proj.lora_down.weight : \n",
495
+ "tensor(1.8857, dtype=torch.float16)\n",
496
+ "lora_unet_double_blocks_8_img_attn_qkv.lora_down.weight : \n",
497
+ "tensor(1.8848, dtype=torch.float16)\n",
498
+ "lora_unet_double_blocks_8_img_mlp_0.lora_down.weight : \n",
499
+ "tensor(1.7627, dtype=torch.float16)\n",
500
+ "lora_unet_double_blocks_8_img_mod_lin.lora_down.weight : \n",
501
+ "tensor(4.2852, dtype=torch.float16)\n",
502
+ "lora_unet_double_blocks_8_txt_attn_proj.lora_down.weight : \n",
503
+ "tensor(1.3887, dtype=torch.float16)\n",
504
+ "lora_unet_double_blocks_8_txt_attn_qkv.lora_down.weight : \n",
505
+ "tensor(1.6289, dtype=torch.float16)\n",
506
+ "lora_unet_double_blocks_8_txt_mlp_0.lora_down.weight : \n",
507
+ "tensor(2.2188, dtype=torch.float16)\n",
508
+ "lora_unet_double_blocks_8_txt_mod_lin.lora_down.weight : \n",
509
+ "tensor(1.5742, dtype=torch.float16)\n",
510
+ "lora_unet_double_blocks_9_img_attn_proj.lora_down.weight : \n",
511
+ "tensor(2.3125, dtype=torch.float16)\n",
512
+ "lora_unet_double_blocks_9_img_attn_qkv.lora_down.weight : \n",
513
+ "tensor(1.4854, dtype=torch.float16)\n",
514
+ "lora_unet_double_blocks_9_img_mlp_0.lora_down.weight : \n",
515
+ "tensor(1.9492, dtype=torch.float16)\n",
516
+ "lora_unet_double_blocks_9_img_mod_lin.lora_down.weight : \n",
517
+ "tensor(2.2949, dtype=torch.float16)\n",
518
+ "lora_unet_double_blocks_9_txt_attn_proj.lora_down.weight : \n",
519
+ "tensor(2.0781, dtype=torch.float16)\n",
520
+ "lora_unet_double_blocks_9_txt_attn_qkv.lora_down.weight : \n",
521
+ "tensor(2.6172, dtype=torch.float16)\n",
522
+ "lora_unet_double_blocks_9_txt_mlp_0.lora_down.weight : \n",
523
+ "tensor(3.1367, dtype=torch.float16)\n",
524
+ "lora_unet_double_blocks_9_txt_mod_lin.lora_down.weight : \n",
525
+ "tensor(1.2451, dtype=torch.float16)\n",
526
+ "lora_unet_single_blocks_0_linear1.lora_down.weight : \n",
527
+ "tensor(2.4375, dtype=torch.float16)\n",
528
+ "lora_unet_single_blocks_0_modulation_lin.lora_down.weight : \n",
529
+ "tensor(3.5684, dtype=torch.float16)\n",
530
+ "lora_unet_single_blocks_10_linear1.lora_down.weight : \n",
531
+ "tensor(2.6328, dtype=torch.float16)\n",
532
+ "lora_unet_single_blocks_10_modulation_lin.lora_down.weight : \n",
533
+ "tensor(2.9961, dtype=torch.float16)\n",
534
+ "lora_unet_single_blocks_11_linear1.lora_down.weight : \n",
535
+ "tensor(3.1211, dtype=torch.float16)\n",
536
+ "lora_unet_single_blocks_11_modulation_lin.lora_down.weight : \n",
537
+ "tensor(3.3672, dtype=torch.float16)\n",
538
+ "lora_unet_single_blocks_12_linear1.lora_down.weight : \n",
539
+ "tensor(3.0293, dtype=torch.float16)\n",
540
+ "lora_unet_single_blocks_12_modulation_lin.lora_down.weight : \n",
541
+ "tensor(3.6602, dtype=torch.float16)\n",
542
+ "lora_unet_single_blocks_13_linear1.lora_down.weight : \n",
543
+ "tensor(2.5918, dtype=torch.float16)\n",
544
+ "lora_unet_single_blocks_13_modulation_lin.lora_down.weight : \n",
545
+ "tensor(4.6367, dtype=torch.float16)\n",
546
+ "lora_unet_single_blocks_14_linear1.lora_down.weight : \n",
547
+ "tensor(2.0215, dtype=torch.float16)\n",
548
+ "lora_unet_single_blocks_14_modulation_lin.lora_down.weight : \n",
549
+ "tensor(3.5371, dtype=torch.float16)\n",
550
+ "lora_unet_single_blocks_15_linear1.lora_down.weight : \n",
551
+ "tensor(2.1719, dtype=torch.float16)\n",
552
+ "lora_unet_single_blocks_15_modulation_lin.lora_down.weight : \n",
553
+ "tensor(4.2812, dtype=torch.float16)\n",
554
+ "lora_unet_single_blocks_16_linear1.lora_down.weight : \n",
555
+ "tensor(2.1992, dtype=torch.float16)\n",
556
+ "lora_unet_single_blocks_16_modulation_lin.lora_down.weight : \n",
557
+ "tensor(4.1094, dtype=torch.float16)\n",
558
+ "lora_unet_single_blocks_17_linear1.lora_down.weight : \n",
559
+ "tensor(2.0703, dtype=torch.float16)\n",
560
+ "lora_unet_single_blocks_17_modulation_lin.lora_down.weight : \n",
561
+ "tensor(2.9277, dtype=torch.float16)\n",
562
+ "lora_unet_single_blocks_18_linear1.lora_down.weight : \n",
563
+ "tensor(2.0371, dtype=torch.float16)\n",
564
+ "lora_unet_single_blocks_18_modulation_lin.lora_down.weight : \n",
565
+ "tensor(2.6133, dtype=torch.float16)\n",
566
+ "lora_unet_single_blocks_19_linear1.lora_down.weight : \n",
567
+ "tensor(2.0723, dtype=torch.float16)\n",
568
+ "lora_unet_single_blocks_19_modulation_lin.lora_down.weight : \n",
569
+ "tensor(3.4980, dtype=torch.float16)\n",
570
+ "lora_unet_single_blocks_1_linear1.lora_down.weight : \n",
571
+ "tensor(1.7432, dtype=torch.float16)\n",
572
+ "lora_unet_single_blocks_1_modulation_lin.lora_down.weight : \n",
573
+ "tensor(2.3848, dtype=torch.float16)\n",
574
+ "lora_unet_single_blocks_20_linear1.lora_down.weight : \n",
575
+ "tensor(2.0137, dtype=torch.float16)\n",
576
+ "lora_unet_single_blocks_20_modulation_lin.lora_down.weight : \n",
577
+ "tensor(2.8203, dtype=torch.float16)\n",
578
+ "lora_unet_single_blocks_21_linear1.lora_down.weight : \n",
579
+ "tensor(1.8955, dtype=torch.float16)\n",
580
+ "lora_unet_single_blocks_21_modulation_lin.lora_down.weight : \n",
581
+ "tensor(2.7305, dtype=torch.float16)\n",
582
+ "lora_unet_single_blocks_22_linear1.lora_down.weight : \n",
583
+ "tensor(2.7559, dtype=torch.float16)\n",
584
+ "lora_unet_single_blocks_22_modulation_lin.lora_down.weight : \n",
585
+ "tensor(4.6133, dtype=torch.float16)\n",
586
+ "lora_unet_single_blocks_23_linear1.lora_down.weight : \n",
587
+ "tensor(2.5508, dtype=torch.float16)\n",
588
+ "lora_unet_single_blocks_23_modulation_lin.lora_down.weight : \n",
589
+ "tensor(4.4180, dtype=torch.float16)\n",
590
+ "lora_unet_single_blocks_24_linear1.lora_down.weight : \n",
591
+ "tensor(1.9219, dtype=torch.float16)\n",
592
+ "lora_unet_single_blocks_24_modulation_lin.lora_down.weight : \n",
593
+ "tensor(2.9453, dtype=torch.float16)\n",
594
+ "lora_unet_single_blocks_25_linear1.lora_down.weight : \n",
595
+ "tensor(2.7539, dtype=torch.float16)\n",
596
+ "lora_unet_single_blocks_25_modulation_lin.lora_down.weight : \n",
597
+ "tensor(4.5938, dtype=torch.float16)\n",
598
+ "lora_unet_single_blocks_26_linear1.lora_down.weight : \n",
599
+ "tensor(3.3750, dtype=torch.float16)\n",
600
+ "lora_unet_single_blocks_26_modulation_lin.lora_down.weight : \n",
601
+ "tensor(4.7344, dtype=torch.float16)\n",
602
+ "lora_unet_single_blocks_27_linear1.lora_down.weight : \n",
603
+ "tensor(2.3809, dtype=torch.float16)\n",
604
+ "lora_unet_single_blocks_27_modulation_lin.lora_down.weight : \n",
605
+ "tensor(4.9883, dtype=torch.float16)\n",
606
+ "lora_unet_single_blocks_28_linear1.lora_down.weight : \n",
607
+ "tensor(3.0859, dtype=torch.float16)\n",
608
+ "lora_unet_single_blocks_28_modulation_lin.lora_down.weight : \n",
609
+ "tensor(5.7539, dtype=torch.float16)\n",
610
+ "lora_unet_single_blocks_29_linear1.lora_down.weight : \n",
611
+ "tensor(2.3242, dtype=torch.float16)\n",
612
+ "lora_unet_single_blocks_29_modulation_lin.lora_down.weight : \n",
613
+ "tensor(3.9160, dtype=torch.float16)\n",
614
+ "lora_unet_single_blocks_2_linear1.lora_down.weight : \n",
615
+ "tensor(2.1406, dtype=torch.float16)\n",
616
+ "lora_unet_single_blocks_2_modulation_lin.lora_down.weight : \n",
617
+ "tensor(2.1621, dtype=torch.float16)\n",
618
+ "lora_unet_single_blocks_30_linear1.lora_down.weight : \n",
619
+ "tensor(2.1211, dtype=torch.float16)\n",
620
+ "lora_unet_single_blocks_30_modulation_lin.lora_down.weight : \n",
621
+ "tensor(4.8516, dtype=torch.float16)\n",
622
+ "lora_unet_single_blocks_31_linear1.lora_down.weight : \n",
623
+ "tensor(2.2773, dtype=torch.float16)\n",
624
+ "lora_unet_single_blocks_31_modulation_lin.lora_down.weight : \n",
625
+ "tensor(4.1367, dtype=torch.float16)\n",
626
+ "lora_unet_single_blocks_32_linear1.lora_down.weight : \n",
627
+ "tensor(2.5273, dtype=torch.float16)\n",
628
+ "lora_unet_single_blocks_32_modulation_lin.lora_down.weight : \n",
629
+ "tensor(5.0508, dtype=torch.float16)\n",
630
+ "lora_unet_single_blocks_33_linear1.lora_down.weight : \n",
631
+ "tensor(2.7051, dtype=torch.float16)\n",
632
+ "lora_unet_single_blocks_33_modulation_lin.lora_down.weight : \n",
633
+ "tensor(5.2930, dtype=torch.float16)\n",
634
+ "lora_unet_single_blocks_34_linear1.lora_down.weight : \n",
635
+ "tensor(2.6738, dtype=torch.float16)\n",
636
+ "lora_unet_single_blocks_34_modulation_lin.lora_down.weight : \n",
637
+ "tensor(4.7852, dtype=torch.float16)\n",
638
+ "lora_unet_single_blocks_35_linear1.lora_down.weight : \n",
639
+ "tensor(2.5117, dtype=torch.float16)\n",
640
+ "lora_unet_single_blocks_35_modulation_lin.lora_down.weight : \n",
641
+ "tensor(6.7734, dtype=torch.float16)\n",
642
+ "lora_unet_single_blocks_36_linear1.lora_down.weight : \n",
643
+ "tensor(1.8418, dtype=torch.float16)\n",
644
+ "lora_unet_single_blocks_36_modulation_lin.lora_down.weight : \n",
645
+ "tensor(6.5859, dtype=torch.float16)\n",
646
+ "lora_unet_single_blocks_37_linear1.lora_down.weight : \n",
647
+ "tensor(2.4473, dtype=torch.float16)\n",
648
+ "lora_unet_single_blocks_37_modulation_lin.lora_down.weight : \n",
649
+ "tensor(2.5742, dtype=torch.float16)\n",
650
+ "lora_unet_single_blocks_3_linear1.lora_down.weight : \n",
651
+ "tensor(2.5566, dtype=torch.float16)\n",
652
+ "lora_unet_single_blocks_3_modulation_lin.lora_down.weight : \n",
653
+ "tensor(4.7148, dtype=torch.float16)\n",
654
+ "lora_unet_single_blocks_4_linear1.lora_down.weight : \n",
655
+ "tensor(2.2832, dtype=torch.float16)\n",
656
+ "lora_unet_single_blocks_4_modulation_lin.lora_down.weight : \n",
657
+ "tensor(2.0566, dtype=torch.float16)\n",
658
+ "lora_unet_single_blocks_5_linear1.lora_down.weight : \n",
659
+ "tensor(2.2109, dtype=torch.float16)\n",
660
+ "lora_unet_single_blocks_5_modulation_lin.lora_down.weight : \n",
661
+ "tensor(2.7793, dtype=torch.float16)\n",
662
+ "lora_unet_single_blocks_6_linear1.lora_down.weight : \n",
663
+ "tensor(3.0176, dtype=torch.float16)\n",
664
+ "lora_unet_single_blocks_6_modulation_lin.lora_down.weight : \n",
665
+ "tensor(2.9180, dtype=torch.float16)\n",
666
+ "lora_unet_single_blocks_7_linear1.lora_down.weight : \n",
667
+ "tensor(2.2461, dtype=torch.float16)\n",
668
+ "lora_unet_single_blocks_7_modulation_lin.lora_down.weight : \n",
669
+ "tensor(2.1074, dtype=torch.float16)\n",
670
+ "lora_unet_single_blocks_8_linear1.lora_down.weight : \n",
671
+ "tensor(3.0391, dtype=torch.float16)\n",
672
+ "lora_unet_single_blocks_8_modulation_lin.lora_down.weight : \n",
673
+ "tensor(2.0039, dtype=torch.float16)\n",
674
+ "lora_unet_single_blocks_9_linear1.lora_down.weight : \n",
675
+ "tensor(3.8789, dtype=torch.float16)\n",
676
+ "lora_unet_single_blocks_9_modulation_lin.lora_down.weight : \n",
677
+ "tensor(4.0547, dtype=torch.float16)\n"
678
+ ]
679
+ }
680
+ ]
681
+ },
682
+ {
683
+ "cell_type": "markdown",
684
+ "source": [
685
+ "<---- Upload your civiai trained .safetensor file to Google Colab before running the next cell\n",
686
+ "\n"
687
+ ],
688
+ "metadata": {
689
+ "id": "oDAUwfFzqzgj"
690
+ }
691
+ },
692
+ {
693
+ "cell_type": "code",
694
+ "execution_count": null,
695
+ "metadata": {
696
+ "id": "WQZ3BZn1p-pw"
697
+ },
698
+ "outputs": [],
699
+ "source": [
700
+ "civiai_lora = '' # @param {type:'string' ,placeholder:'ex. civitai_trained_e19.safetensors'}\n",
701
+ "tensor_art_filename = '' # @param {type:'string' ,placeholder:'ex. e19.safetensors'}\n",
702
+ "%cd /content/\n",
703
+ "tgt = load_file(f'{civiai_lora}')\n",
704
+ "for key in tgt:\n",
705
+ " tgt[f'{key}'] = tgt[f'{key}'].to(dtype=torch.float16)\n",
706
+ "%cd /content/\n",
707
+ "save_file(tgt , f'{tensor_art_filename}')"
708
+ ]
709
+ },
710
+ {
711
+ "cell_type": "markdown",
712
+ "source": [
713
+ "Download the new .safetensor file to your device.\n",
714
+ "\n",
715
+ "Downloading from CoLab Notebook will seemingly do nothing for ~5min. Then the file will download , so be patient.\n",
716
+ "\n",
717
+ "For faster/more consistent downloads , download your .safetensor file from your Google Drive"
718
+ ],
719
+ "metadata": {
720
+ "id": "blnBW-U4rAS7"
721
+ }
722
+ }
723
+ ]
724
+ }