Instructions to use NbAiLab/roberta_jan_128_ncc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLab/roberta_jan_128_ncc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NbAiLab/roberta_jan_128_ncc")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NbAiLab/roberta_jan_128_ncc") model = AutoModelForMaskedLM.from_pretrained("NbAiLab/roberta_jan_128_ncc") - Notebooks
- Google Colab
- Kaggle
Saving weights and logs of step 136000
Browse files
events.out.tfevents.1642861064.t1v-n-ccbf3e94-w-0.1931366.3.v2
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 sha256:3ceeb8aedc544ddbee4beab4cd443a917ff6919c9af17f390ab6579ed90c6c1c
|
| 3 |
+
size 19826802
|
flax_model.msgpack
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 498796983
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:f69461b1af3f980761031397def584dd50c936a2fb87f8f7a5692093d1d144d8
|
| 3 |
size 498796983
|