Instructions to use Sayan01/tiny-bert-qnli-distilled with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sayan01/tiny-bert-qnli-distilled with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sayan01/tiny-bert-qnli-distilled")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sayan01/tiny-bert-qnli-distilled") model = AutoModelForSequenceClassification.from_pretrained("Sayan01/tiny-bert-qnli-distilled", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 43
Browse files
logs/events.out.tfevents.1656871022.23acfda42b08.7187.0
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:cafebf6abbf76712ba1f73a53bdbfe9ea92f78c71d932ab2f521b00258705039
|
| 3 |
+
size 24705
|
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 sha256:4937c09689a26010971f8c92ca2857f38e5f6c5be39f842c43f697c6109d751b
|
| 3 |
size 57430535
|