Text Classification
Transformers
PyTorch
TensorBoard
albert
Generated from Trainer
Eval Results (legacy)
Instructions to use jiiyy/albert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jiiyy/albert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jiiyy/albert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jiiyy/albert") model = AutoModelForSequenceClassification.from_pretrained("jiiyy/albert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
End of training
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 52762690
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:9c8ca991bb7db54299144ce47477eacb173f2d891d52fc9c37028ff239efadf2
|
| 3 |
size 52762690
|
runs/Aug16_05-33-48_7b48932c89e9/events.out.tfevents.1692164151.7b48932c89e9.290.0
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:fe8272842bd879398c012494147b10214c270a742b7736eef30cfae983a1b697
|
| 3 |
+
size 14420
|