Instructions to use tawsif18/puma_model_checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use tawsif18/puma_model_checkpoints with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://tawsif18/puma_model_checkpoints") - Notebooks
- Google Colab
- Kaggle
Checkpoint sharp_nuclei_epoch225_datasetsize16000_fullmodel.keras
Browse files
.gitattributes
CHANGED
|
@@ -282,3 +282,4 @@ sharp_nuclei_epoch215_datasetsize16000_fullmodel.keras filter=lfs diff=lfs merge
|
|
| 282 |
multires_nuclei_epoch40_datasetsize16000_fullmodel.keras filter=lfs diff=lfs merge=lfs -text
|
| 283 |
sharp_nuclei_epoch220_datasetsize16000_fullmodel.keras filter=lfs diff=lfs merge=lfs -text
|
| 284 |
multires_nuclei_epoch45_datasetsize16000_fullmodel.keras filter=lfs diff=lfs merge=lfs -text
|
|
|
|
|
|
| 282 |
multires_nuclei_epoch40_datasetsize16000_fullmodel.keras filter=lfs diff=lfs merge=lfs -text
|
| 283 |
sharp_nuclei_epoch220_datasetsize16000_fullmodel.keras filter=lfs diff=lfs merge=lfs -text
|
| 284 |
multires_nuclei_epoch45_datasetsize16000_fullmodel.keras filter=lfs diff=lfs merge=lfs -text
|
| 285 |
+
sharp_nuclei_epoch225_datasetsize16000_fullmodel.keras filter=lfs diff=lfs merge=lfs -text
|
sharp_nuclei_epoch225_datasetsize16000_fullmodel.keras
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:6a8ad21f1524858e0a035881a7345543e032cc3d1d640d38a136ec66ca42a590
|
| 3 |
+
size 753620135
|