Image Classification
PyTorch
Safetensors
Transformers
English
resnet10
feature-extraction
jax-conversion
resnet
hil-serl
Lerobot
vision
custom_code
Instructions to use lilkm/resnet10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lilkm/resnet10 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="lilkm/resnet10", 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("lilkm/resnet10", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Upload ResNet10
Browse files- config.json +6 -1
config.json
CHANGED
|
@@ -1,6 +1,10 @@
|
|
| 1 |
{
|
|
|
|
|
|
|
|
|
|
| 2 |
"auto_map": {
|
| 3 |
-
"AutoConfig": "configuration_resnet.ResNet10Config"
|
|
|
|
| 4 |
},
|
| 5 |
"depths": [
|
| 6 |
1,
|
|
@@ -8,6 +12,7 @@
|
|
| 8 |
1,
|
| 9 |
1
|
| 10 |
],
|
|
|
|
| 11 |
"embedding_size": 64,
|
| 12 |
"hidden_act": "relu",
|
| 13 |
"hidden_sizes": [
|
|
|
|
| 1 |
{
|
| 2 |
+
"architectures": [
|
| 3 |
+
"ResNet10"
|
| 4 |
+
],
|
| 5 |
"auto_map": {
|
| 6 |
+
"AutoConfig": "configuration_resnet.ResNet10Config",
|
| 7 |
+
"AutoModel": "modeling_resnet.ResNet10"
|
| 8 |
},
|
| 9 |
"depths": [
|
| 10 |
1,
|
|
|
|
| 12 |
1,
|
| 13 |
1
|
| 14 |
],
|
| 15 |
+
"dtype": "float32",
|
| 16 |
"embedding_size": 64,
|
| 17 |
"hidden_act": "relu",
|
| 18 |
"hidden_sizes": [
|