Instructions to use textattack/roberta-base-rotten-tomatoes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textattack/roberta-base-rotten-tomatoes with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="textattack/roberta-base-rotten-tomatoes")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textattack/roberta-base-rotten-tomatoes") model = AutoModelForSequenceClassification.from_pretrained("textattack/roberta-base-rotten-tomatoes") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -1,5 +1,4 @@
|
|
| 1 |
-
##
|
| 2 |
-
|
| 3 |
This `roberta-base` model was fine-tuned for sequence classificationusing TextAttack
|
| 4 |
and the rotten_tomatoes dataset loaded using the `nlp` library. The model was fine-tuned
|
| 5 |
for 10 epochs with a batch size of 64, a learning
|
|
|
|
| 1 |
+
## TextAttack Model Card
|
|
|
|
| 2 |
This `roberta-base` model was fine-tuned for sequence classificationusing TextAttack
|
| 3 |
and the rotten_tomatoes dataset loaded using the `nlp` library. The model was fine-tuned
|
| 4 |
for 10 epochs with a batch size of 64, a learning
|