upload safetensors and conversion script

convert_pt.py

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+from safetensors.torch import save_file
+import torch
+from torchvision.models import resnet34
+
+model_path = "RESNET_34_cancer_350px_lr_1e-2_decay_5_jitter_val6slides_harder_tcga_none_0403_0204_0.9826153355179645_16.t7"
+
+orig_model = torch.load(model_path, map_location="cpu")
+state_dict = orig_model["model"].module.state_dict()
+keys_missing = [
+    "bn1.num_batches_tracked",
+    "layer1.0.bn1.num_batches_tracked",
+    "layer1.0.bn2.num_batches_tracked",
+    "layer1.1.bn1.num_batches_tracked",
+    "layer1.1.bn2.num_batches_tracked",
+    "layer1.2.bn1.num_batches_tracked",
+    "layer1.2.bn2.num_batches_tracked",
+    "layer2.0.bn1.num_batches_tracked",
+    "layer2.0.bn2.num_batches_tracked",
+    "layer2.0.downsample.1.num_batches_tracked",
+    "layer2.1.bn1.num_batches_tracked",
+    "layer2.1.bn2.num_batches_tracked",
+    "layer2.2.bn1.num_batches_tracked",
+    "layer2.2.bn2.num_batches_tracked",
+    "layer2.3.bn1.num_batches_tracked",
+    "layer2.3.bn2.num_batches_tracked",
+    "layer3.0.bn1.num_batches_tracked",
+    "layer3.0.bn2.num_batches_tracked",
+    "layer3.0.downsample.1.num_batches_tracked",
+    "layer3.1.bn1.num_batches_tracked",
+    "layer3.1.bn2.num_batches_tracked",
+    "layer3.2.bn1.num_batches_tracked",
+    "layer3.2.bn2.num_batches_tracked",
+    "layer3.3.bn1.num_batches_tracked",
+    "layer3.3.bn2.num_batches_tracked",
+    "layer3.4.bn1.num_batches_tracked",
+    "layer3.4.bn2.num_batches_tracked",
+    "layer3.5.bn1.num_batches_tracked",
+    "layer3.5.bn2.num_batches_tracked",
+    "layer4.0.bn1.num_batches_tracked",
+    "layer4.0.bn2.num_batches_tracked",
+    "layer4.0.downsample.1.num_batches_tracked",
+    "layer4.1.bn1.num_batches_tracked",
+    "layer4.1.bn2.num_batches_tracked",
+    "layer4.2.bn1.num_batches_tracked",
+    "layer4.2.bn2.num_batches_tracked",
+]
+assert not any(
+    key in state_dict.keys() for key in keys_missing
+), "key present that should be missing"
+for key in keys_missing:
+    state_dict[key] = torch.as_tensor(0)
+torch.save(state_dict, "pytorch_model.pt")
+save_file(state_dict, "model.safetensors")
+
+model = resnet34(weights=None)
+model.fc = torch.nn.Linear(model.fc.in_features, out_features=5, bias=True)
+model.load_state_dict(state_dict)
+model_jit = torch.jit.script(model, example_inputs=[(torch.ones(1, 3, 224, 224),)])
+torch.jit.save(model_jit, "torchscript_model.bin")

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:c22f2594a277db430a58896ccc1fa751435c6054e09fc825e5a5534af70f7ae3
+size 85236652