Instructions to use autoevaluate/roberta-base-squad2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use autoevaluate/roberta-base-squad2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="autoevaluate/roberta-base-squad2")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("autoevaluate/roberta-base-squad2") model = AutoModelForQuestionAnswering.from_pretrained("autoevaluate/roberta-base-squad2") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -7,6 +7,8 @@ license: cc-by-4.0
|
|
| 7 |
|
| 8 |
# roberta-base for QA
|
| 9 |
|
|
|
|
|
|
|
| 10 |
This is the [roberta-base](https://huggingface.co/roberta-base) model, fine-tuned using the [SQuAD2.0](https://huggingface.co/datasets/squad_v2) dataset. It's been trained on question-answer pairs, including unanswerable questions, for the task of Question Answering.
|
| 11 |
|
| 12 |
|
|
|
|
| 7 |
|
| 8 |
# roberta-base for QA
|
| 9 |
|
| 10 |
+
> Note: this is a clone of [`roberta-base-squad2`](https://huggingface.co/deepset/roberta-base-squad2) for internal testing.
|
| 11 |
+
|
| 12 |
This is the [roberta-base](https://huggingface.co/roberta-base) model, fine-tuned using the [SQuAD2.0](https://huggingface.co/datasets/squad_v2) dataset. It's been trained on question-answer pairs, including unanswerable questions, for the task of Question Answering.
|
| 13 |
|
| 14 |
|