Instructions to use ShengdingHu/rte with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ShengdingHu/rte with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ShengdingHu/rte") model = AutoModelForSeq2SeqLM.from_pretrained("ShengdingHu/rte", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
8bd16ad
1
Parent(s): 581cafa
Training in progress, epoch 9
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 7221369
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:f5869f9426aa4ba299ec8eb6333dc547808f230889e0bfb27b2acdff703ebfab
|
| 3 |
size 7221369
|
runs/Jan29_14-32-47_node4/events.out.tfevents.1643437989.node4
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 sha256:5a73f6b75b58a21cd97c706fa15248cd850a0ec9ca12d0ea8e257bddc874bc7f
|
| 3 |
+
size 6250
|