Instructions to use versae/roberta-base-ncc-512c with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use versae/roberta-base-ncc-512c with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="versae/roberta-base-ncc-512c")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("versae/roberta-base-ncc-512c") model = AutoModelForMaskedLM.from_pretrained("versae/roberta-base-ncc-512c") - Notebooks
- Google Colab
- Kaggle
Testing lr 3e-5
Browse files- run_mlm_flax.py +1 -1
run_mlm_flax.py
CHANGED
|
@@ -553,7 +553,7 @@ def main():
|
|
| 553 |
wandb.init(
|
| 554 |
entity='versae',
|
| 555 |
project='roberta-base-ncc',
|
| 556 |
-
sync_tensorboard=
|
| 557 |
)
|
| 558 |
wandb.config.update(training_args)
|
| 559 |
wandb.config.update(model_args)
|
|
|
|
| 553 |
wandb.init(
|
| 554 |
entity='versae',
|
| 555 |
project='roberta-base-ncc',
|
| 556 |
+
sync_tensorboard=True,
|
| 557 |
)
|
| 558 |
wandb.config.update(training_args)
|
| 559 |
wandb.config.update(model_args)
|