Instructions to use tanjina284/puma_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use tanjina284/puma_model with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://tanjina284/puma_model") - Notebooks
- Google Colab
- Kaggle
Checkpoint attention_nuclei_epoch70_datasetsize16000_fullmodel.keras
Browse files
.gitattributes
CHANGED
|
@@ -355,3 +355,4 @@ attention_nuclei_epoch65_datasetsize16000_fullmodel.keras filter=lfs diff=lfs me
|
|
| 355 |
deeplab_nuclei_epoch5_datasetsize16000_fullmodel.keras filter=lfs diff=lfs merge=lfs -text
|
| 356 |
sharp_nuclei_epoch60_datasetsize16000_fullmodel.keras filter=lfs diff=lfs merge=lfs -text
|
| 357 |
unet_nuclei_epoch85_datasetsize16000_fullmodel.keras filter=lfs diff=lfs merge=lfs -text
|
|
|
|
|
|
| 355 |
deeplab_nuclei_epoch5_datasetsize16000_fullmodel.keras filter=lfs diff=lfs merge=lfs -text
|
| 356 |
sharp_nuclei_epoch60_datasetsize16000_fullmodel.keras filter=lfs diff=lfs merge=lfs -text
|
| 357 |
unet_nuclei_epoch85_datasetsize16000_fullmodel.keras filter=lfs diff=lfs merge=lfs -text
|
| 358 |
+
attention_nuclei_epoch70_datasetsize16000_fullmodel.keras filter=lfs diff=lfs merge=lfs -text
|
attention_nuclei_epoch70_datasetsize16000_fullmodel.keras
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:09603da155dc8c0b21fa5ee896cd77f549cb87c3ac02e78619a734cce235e3f9
|
| 3 |
+
size 656277257
|