Instructions to use bn22/my-timm-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use bn22/my-timm-model with timm:
import timm model = timm.create_model("hf_hub:bn22/my-timm-model", pretrained=True) - Transformers
How to use bn22/my-timm-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="bn22/my-timm-model") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("bn22/my-timm-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Add model
Browse files- config.json +1 -2
- model.safetensors +2 -2
- pytorch_model.bin +2 -2
config.json
CHANGED
|
@@ -1,8 +1,7 @@
|
|
| 1 |
{
|
| 2 |
"architecture": "naflexvit_base_patch16_siglip",
|
| 3 |
-
"num_classes":
|
| 4 |
"num_features": 384,
|
| 5 |
-
"embed_dim": 384,
|
| 6 |
"global_pool": "map",
|
| 7 |
"pretrained_cfg": {
|
| 8 |
"tag": "v2_webli",
|
|
|
|
| 1 |
{
|
| 2 |
"architecture": "naflexvit_base_patch16_siglip",
|
| 3 |
+
"num_classes": 0,
|
| 4 |
"num_features": 384,
|
|
|
|
| 5 |
"global_pool": "map",
|
| 6 |
"pretrained_cfg": {
|
| 7 |
"tag": "v2_webli",
|
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:0fb1875f60a055f3b36537d32e91c4dec673d3449e706284903fe496aef2f967
|
| 3 |
+
size 93864448
|
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:48c42ebbd3d23e0fda65b4ee76fb31ba2cb0ac0c94b3954d0144471e1318a9bf
|
| 3 |
+
size 93916331
|