Instructions to use ivensamdh/gender with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ivensamdh/gender with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ivensamdh/gender") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("ivensamdh/gender") model = AutoModelForImageClassification.from_pretrained("ivensamdh/gender", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Model save
Browse files- pytorch_model.bin +1 -1
- training_args.bin +1 -1
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 86733677
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:7250cec7638c1ad8ba4b444c3c0e13b30c33f0383c3162f6267813008944b464
|
| 3 |
size 86733677
|
training_args.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 3515
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:593408a715810d662895efb4dd864aca3272000ff35cdbc709af0f0cd4d4c98c
|
| 3 |
size 3515
|