Instructions to use nkhamm/checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nkhamm/checkpoints with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("nkhamm/checkpoints") model = AutoModelForSeq2SeqLM.from_pretrained("nkhamm/checkpoints") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 2000
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 1518942685
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:23aa3fee0906ceecddfbc241c3466452bff73294ac377adaa42f118e17fa6532
|
| 3 |
size 1518942685
|
runs/Jun23_21-26-10_baac70d2399f/events.out.tfevents.1687555572.baac70d2399f.64429.5
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 sha256:671333e6badcddeebb4d0737c10ab941755837b060a7b4060d25612198333d86
|
| 3 |
+
size 320814
|