Instructions to use FredZhang7/efficientnetv25_rw_s with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FredZhang7/efficientnetv25_rw_s with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="FredZhang7/efficientnetv25_rw_s", trust_remote_code=True) pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("FredZhang7/efficientnetv25_rw_s", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:efeb86064f68ef4729eabdcd5cefdc0f1bf981ae03e603b17b916b506e1cb4ae
|
| 3 |
+
size 256
|