Instructions to use Sayan01/tiny-bert-stsb-distilled with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sayan01/tiny-bert-stsb-distilled with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sayan01/tiny-bert-stsb-distilled")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sayan01/tiny-bert-stsb-distilled") model = AutoModelForSequenceClassification.from_pretrained("Sayan01/tiny-bert-stsb-distilled", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 13
Browse files
logs/events.out.tfevents.1656838513.6d65cfcd351c.80.8
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:bfc7350822b27a5cf27ac7b2b1de099c1110d99011e3c0bdb8762d15ccbd73a0
|
| 3 |
+
size 10647
|
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 57429255
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:3ed35b138a283415dcdfef3b858c675b4ef8ce1a0614015080409589f99081b6
|
| 3 |
size 57429255
|