Instructions to use Sayan01/tiny-bert-mrpc-distilled with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sayan01/tiny-bert-mrpc-distilled with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sayan01/tiny-bert-mrpc-distilled")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sayan01/tiny-bert-mrpc-distilled") model = AutoModelForSequenceClassification.from_pretrained("Sayan01/tiny-bert-mrpc-distilled") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
Browse files
logs/1655980824.6563725/events.out.tfevents.1655980824.9fd42316f55c.73.25
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:6ebb658e83190985a7c44c5af53428652bbec1a445200abfa803e5140e5860a2
|
| 3 |
+
size 5347
|
logs/events.out.tfevents.1655980750.9fd42316f55c.73.22
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 sha256:913c98913d177fe0eb59ae8221235f0060a4fb219456400955095884b1821bf2
|
| 3 |
+
size 5118
|
logs/events.out.tfevents.1655980824.9fd42316f55c.73.24
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:218dfe1a1de98b8abbb5691dfc6ccdda74b7a3328f0c71c780cd2ed270206889
|
| 3 |
+
size 4158
|
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 sha256:5b6622b39aa3b2e43fd406fd7113af6f958f70421cf1b07e78441c9497b96f5a
|
| 3 |
size 17561831
|