Instructions to use Rustem/distilroberta-base-trained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rustem/distilroberta-base-trained with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Rustem/distilroberta-base-trained")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Rustem/distilroberta-base-trained") model = AutoModelForMaskedLM.from_pretrained("Rustem/distilroberta-base-trained", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload optimizer.pt with git-lfs
Browse files- optimizer.pt +3 -0
optimizer.pt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:9c791f643134cce1bc97edeede320c742544db924e26f5d8bbc15569b5cb4c5d
|
| 3 |
+
size 657422681
|