2809

src/cherrypick.ipynb

@@ -1452,7 +1452,7 @@
     "pipeid = \"AiArtLab/sdxs\"\n",
     "variant = \"fp16\" if torch.cuda.is_available() else None\n",
     "\n",
-    "unet = UNet2DConditionModel.from_pretrained(\"/workspace/sdxs\"#pipeid\n",
+    "unet = UNet2DConditionModel.from_pretrained(\"/workspace/sdxs3d\"#pipeid\n",
     "                                            , subfolder=\"unet\", variant=variant).to(device, dtype=dtype).eval()\n",
     "vae = AutoencoderKL.from_pretrained(pipeid, subfolder=\"vae\", variant=variant).to(device, dtype=dtype).eval()\n",
     "scheduler = DDPMScheduler.from_pretrained(pipeid, subfolder=\"scheduler\")\n",
@@ -1577,7 +1577,7 @@
     "    print(\"Images generated and saved to:\", output_folder)\n",
     "\n",
     "# Example usage\n",
-    "dataset_path = \"/workspace/sdxs/datasets/576\"\n",
+    "dataset_path = \"/workspace/sdxs3d/datasets/mjnj\"\n",
     "generate_and_save_images(dataset_path)\n"
    ]
   },
@@ -1606,7 +1606,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.10"
+   "version": "3.11.11"
   }
  },
  "nbformat": 4,

train.py

@@ -28,9 +28,9 @@ from collections import deque
 # --------------------------- Параметры ---------------------------
 ds_path = "/workspace/sdxs3d/datasets/mjnj"
 project = "unet"
-batch_size = 128
-base_learning_rate = 8e-5
-min_learning_rate = 2e-5
+batch_size = 96
+base_learning_rate = 6e-5
+min_learning_rate = 9e-6
 num_epochs = 50
 # samples/save per epoch
 sample_interval_share = 5

unet/diffusion_pytorch_model.fp16.safetensors

@@ -1,3 +0,0 @@
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-oid sha256:072a5932b339f1c98d492fe71c74a374de6c0e5480dab5f0c393aed03818b6e1
-size 3092571208

unet/diffusion_pytorch_model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:958b8d4d7c0c89ddd9977f61f3d17bb2dd5027b75c0d3669c30d55cf448d5c94
-size 6184944280
+oid sha256:072a5932b339f1c98d492fe71c74a374de6c0e5480dab5f0c393aed03818b6e1
+size 3092571208