Instructions to use srcocotero/bert-qa-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use srcocotero/bert-qa-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="srcocotero/bert-qa-en")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("srcocotero/bert-qa-en") model = AutoModelForQuestionAnswering.from_pretrained("srcocotero/bert-qa-en") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Add base_model information to model
#2
by librarian-bot - opened
README.md
CHANGED
|
@@ -4,6 +4,7 @@ tags:
|
|
| 4 |
- generated_from_trainer
|
| 5 |
datasets:
|
| 6 |
- squad
|
|
|
|
| 7 |
model-index:
|
| 8 |
- name: bert-qa-en
|
| 9 |
results: []
|
|
|
|
| 4 |
- generated_from_trainer
|
| 5 |
datasets:
|
| 6 |
- squad
|
| 7 |
+
base_model: bert-base-uncased
|
| 8 |
model-index:
|
| 9 |
- name: bert-qa-en
|
| 10 |
results: []
|