Instructions to use Sayan01/tiny-bert-mnli-distilled with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sayan01/tiny-bert-mnli-distilled with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sayan01/tiny-bert-mnli-distilled")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sayan01/tiny-bert-mnli-distilled") model = AutoModelForSequenceClassification.from_pretrained("Sayan01/tiny-bert-mnli-distilled", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
Browse files
logs/1657128230.3813446/events.out.tfevents.1657128230.9181eea70df4.83.3
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:71879a7a0de603053fdab0da2400ea1cf61409545a05e74b4738c8c501676e04
|
| 3 |
+
size 5347
|
logs/events.out.tfevents.1657128230.9181eea70df4.83.2
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:1e9909adc4b9c03577b859026fdc0f11d95d1a01382e3984dfcdb879d910e322
|
| 3 |
+
size 4209
|
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 17562343
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:21a01b58c8fefce36cc2f6e39bca24423c9ec899765205325e6bc47720a01297
|
| 3 |
size 17562343
|
training_args.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 3375
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:8bc8e034a63a7d269b99b8ce79236a0660ffaf930d20262f086b632f7ea77c95
|
| 3 |
size 3375
|