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:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("nkhamm/checkpoints") model = AutoModelForSeq2SeqLM.from_pretrained("nkhamm/checkpoints", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 3000
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 sha256:05d39f306b2b3a24631887e44b686b507b92d8f735d7ecdb0c8fe8899671fc79
|
| 3 |
size 1518942685
|
runs/Jun24_13-52-53_e5646bb0120a/events.out.tfevents.1687614778.e5646bb0120a.39801.0
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:db90569d2e16080b26ab7d7641f35e4dca85dc988d233f66e999ec3b3035e1f0
|
| 3 |
+
size 477746
|