Instructions to use jesschiang/tmp_trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jesschiang/tmp_trainer with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jesschiang/tmp_trainer", dtype="auto") - Notebooks
- Google Colab
- Kaggle
End of training
Browse files- adapter_model.safetensors +1 -1
- training_args.bin +1 -1
adapter_model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 13648432
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:76f7809ec3aabae466042d4cac14f9df26be7cdcf77a406846114e44c49ec4c9
|
| 3 |
size 13648432
|
training_args.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 5560
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:52beba79d325b51cbde25313bafdf4dc45192711e6b5ba72131e76d61b50c2f4
|
| 3 |
size 5560
|