Instructions to use dexforint/train_result with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dexforint/train_result with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="dexforint/train_result")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("dexforint/train_result") model = AutoModelForObjectDetection.from_pretrained("dexforint/train_result", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 27600
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 166616101
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:431235b5afe17775cf5ad34b8977e0cb13de473eda87e66084c400cb80c76c62
|
| 3 |
size 166616101
|
runs/Jun15_09-37-17_c4ffc44ffa48/events.out.tfevents.1686821929.c4ffc44ffa48.24.0
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:cd8edcee57975a53d2ffe94b604e9f26310b89008f815d32e203451a1a0bad4a
|
| 3 |
+
size 91992
|