# Load model directly
from transformers import AutoImageProcessor, SegformerForSemanticSegmentation
processor = AutoImageProcessor.from_pretrained("Isaacks/test_push")
model = SegformerForSemanticSegmentation.from_pretrained("Isaacks/test_push")Quick Links
test_push
This model is a fine-tuned version of Isaacks/test_push on the Isaacks/ihc_slide_tissue dataset.
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1
- Datasets 2.14.3
- Tokenizers 0.13.3
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="Isaacks/test_push")