Instructions to use Sayan01/tiny-bert-rte-distilled with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sayan01/tiny-bert-rte-distilled with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sayan01/tiny-bert-rte-distilled")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sayan01/tiny-bert-rte-distilled") model = AutoModelForSequenceClassification.from_pretrained("Sayan01/tiny-bert-rte-distilled", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
Browse files
logs/1655996476.776833/events.out.tfevents.1655996476.9fd42316f55c.73.45
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:231f5b0d7fa93711d312b2f3a758622a3d156e16d8c8709c78c62f7dd5c98d66
|
| 3 |
+
size 5343
|
logs/events.out.tfevents.1655996476.9fd42316f55c.73.44
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:23f46cbc4767be91db524ef5e2630a961264c1ddc1a9af2a73607fe5bc991512
|
| 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:f22d5da86ea34988b486cfca00636ac4400df89278d9775a7aa7f423736bf508
|
| 3 |
size 17561831
|