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 80000
Browse files
events.out.tfevents.1643149905.t1v-n-ccbf3e94-w-0.2231714.3.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 sha256:41ece0e8593804f5379f7ec6870fb3b67e7488d1cb421049c990d00fbb5c45c9
|
| 3 |
+
size 11757457
|
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:f26e374e72121c77dec5f9186e3ef4f45cef183f9244d0c19a39416030761516
|
| 3 |
size 498796983
|