Instructions to use Sayan01/tiny-bert-qqp-distilled with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sayan01/tiny-bert-qqp-distilled with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sayan01/tiny-bert-qqp-distilled")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sayan01/tiny-bert-qqp-distilled") model = AutoModelForSequenceClassification.from_pretrained("Sayan01/tiny-bert-qqp-distilled", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 5
Browse files
logs/events.out.tfevents.1656608020.dc9e1672c50e.2147.22
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 sha256:04cf0ed519f7abb03b7d48baab18a5fdbe223f523f348504d3fdc1ca4c2ce685
|
| 3 |
+
size 6388
|
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 57430535
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:b84bf141269f33005e5caba194b0e816a56275bb67d368fc6d1014d2acc1f44b
|
| 3 |
size 57430535
|