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:
# pip install -U transformers accelerate # 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 ·
dce0403
1
Parent(s): 4177ce7
Training in progress, step 300
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 2631685
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:720ed4c356c7ec3bd44cefe35db0b46a0f934428afa62624a94e10fc7ef02482
|
| 3 |
size 2631685
|
runs/Feb02_15-36-39_node1/events.out.tfevents.1643787523.node1
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:d811c48d7b28701089d959ff6584cdd335042ee50a327f76320f1335436356a8
|
| 3 |
+
size 4935
|