Push model using huggingface_hub.
Browse files- README.md +4 -4
- model.safetensors +1 -1
README.md
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@@ -19,7 +19,7 @@ parameters: "dataloader:\n num_workers: 0\ndataset:\n datasets:\n test_weed
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\ student:\n name: conv_distillator\n num_classes: 2\n teacher:\n\
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\ backbone: swin\n backbone_checkpoint: checkpoints/swin_base_patch4_window12_384.pth\n\
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\ concat_support: false\n image_size: 384\n model_checkpoint: checkpoints/swin_fold0_pascal_modcross_soft.pt\n\
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\ name: dcama\npush_to_hub:\n repo_name: DistillFSS_WeedMap_DCAMA_5shot\n\
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refinement:\n hot_parameters:\n - model.conv1\n - model.conv2\n - model.conv3\n\
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\ - model.mixer1\n - model.mixer2\n - model.mixer3\n - student\n iterations_is_num_classes:\
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\ false\n loss:\n name: refine_distill\n lr: 0.001\n max_iterations: 500\n\
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@@ -27,7 +27,7 @@ parameters: "dataloader:\n num_workers: 0\ndataset:\n datasets:\n test_weed
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\ cache_dir: tmp\n group: WeedMap\n log_frequency: 1\n project: FSSWeed\n tags:\n\
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\ - WeedMap\n - Distill\n test_image_log_frequency: 10\n tmp_dir: tmp\n train_image_log_frequency:\
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\ 25\n"
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repo_id: DistillFSS_WeedMap_DCAMA_5shot
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---
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DistillFSS-DCAMA is a distilled version of the DCAMA model for a specific downstream segmentation task. The DistillFSS framework allows to distill large few-shot segmentation models into smaller and more efficient ones, while improving or maintaining their performance on the target task.
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@@ -45,7 +45,7 @@ Install the required dependencies as specified in the repository.
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Load the model using the following code snippet:
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```python
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from distillfss.models.dcama.distillator import DistilledDCAMA
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model = DistilledDCAMA.from_pretrained("DistillFSS_WeedMap_DCAMA_5shot")
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```
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YAML configuration:
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@@ -82,7 +82,7 @@ model:
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model_checkpoint: checkpoints/swin_fold0_pascal_modcross_soft.pt
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name: dcama
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push_to_hub:
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repo_name: DistillFSS_WeedMap_DCAMA_5shot
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refinement:
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hot_parameters:
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- model.conv1
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\ student:\n name: conv_distillator\n num_classes: 2\n teacher:\n\
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\ backbone: swin\n backbone_checkpoint: checkpoints/swin_base_patch4_window12_384.pth\n\
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\ concat_support: false\n image_size: 384\n model_checkpoint: checkpoints/swin_fold0_pascal_modcross_soft.pt\n\
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\ name: dcama\npush_to_hub:\n repo_name: pasqualedem/DistillFSS_WeedMap_DCAMA_5shot\n\
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refinement:\n hot_parameters:\n - model.conv1\n - model.conv2\n - model.conv3\n\
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\ - model.mixer1\n - model.mixer2\n - model.mixer3\n - student\n iterations_is_num_classes:\
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\ false\n loss:\n name: refine_distill\n lr: 0.001\n max_iterations: 500\n\
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\ cache_dir: tmp\n group: WeedMap\n log_frequency: 1\n project: FSSWeed\n tags:\n\
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\ - WeedMap\n - Distill\n test_image_log_frequency: 10\n tmp_dir: tmp\n train_image_log_frequency:\
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\ 25\n"
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repo_id: pasqualedem/DistillFSS_WeedMap_DCAMA_5shot
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---
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DistillFSS-DCAMA is a distilled version of the DCAMA model for a specific downstream segmentation task. The DistillFSS framework allows to distill large few-shot segmentation models into smaller and more efficient ones, while improving or maintaining their performance on the target task.
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Load the model using the following code snippet:
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```python
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from distillfss.models.dcama.distillator import DistilledDCAMA
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model = DistilledDCAMA.from_pretrained("pasqualedem/DistillFSS_WeedMap_DCAMA_5shot")
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```
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YAML configuration:
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model_checkpoint: checkpoints/swin_fold0_pascal_modcross_soft.pt
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name: dcama
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push_to_hub:
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repo_name: pasqualedem/DistillFSS_WeedMap_DCAMA_5shot
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refinement:
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hot_parameters:
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- model.conv1
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model.safetensors
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size 554599424
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version https://git-lfs.github.com/spec/v1
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size 554599424
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