Instructions to use Shravanig/vit-fire-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shravanig/vit-fire-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Shravanig/vit-fire-detection") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("Shravanig/vit-fire-detection") model = AutoModelForImageClassification.from_pretrained("Shravanig/vit-fire-detection") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 6
Browse files
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 343227052
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:68deb4344c43ec42d49a4f1a84836da37db9ded3a52b9a7cedbc50ba485caabc
|
| 3 |
size 343227052
|
runs/Feb12_17-23-13_Shravani/events.out.tfevents.1707738794.Shravani.49728.0
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 sha256:7682a8a7563f083ad70ea0cc6baad006f0e12caef7d9a3455a68c4c2c0cc45e2
|
| 3 |
+
size 8995
|