Instructions to use Sayan01/tiny-bert-sst2-distilled with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sayan01/tiny-bert-sst2-distilled with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sayan01/tiny-bert-sst2-distilled")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sayan01/tiny-bert-sst2-distilled") model = AutoModelForSequenceClassification.from_pretrained("Sayan01/tiny-bert-sst2-distilled", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 6
Browse files
logs/events.out.tfevents.1655842194.4dede0cb6010.74.46
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:bca9767a77616964bb3168c8b2bd1e828706bcccd0ea64abe76942d7bcc99b43
|
| 3 |
+
size 6694
|
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 17561831
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:25b4076ce53910cd8c1a75074346c457efa43dd28eca16ea06203b453010908f
|
| 3 |
size 17561831
|