Table Question Answering
Transformers
PyTorch
Safetensors
English
bart
text2text-generation
multitabqa
multi-table-question-answering
Instructions to use vaishali/multitabqa-base-atis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vaishali/multitabqa-base-atis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("table-question-answering", model="vaishali/multitabqa-base-atis")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("vaishali/multitabqa-base-atis") model = AutoModelForSeq2SeqLM.from_pretrained("vaishali/multitabqa-base-atis") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -5,6 +5,8 @@ tags:
|
|
| 5 |
- multi-table-question-answering
|
| 6 |
license: mit
|
| 7 |
pipeline_tag: table-question-answering
|
|
|
|
|
|
|
| 8 |
---
|
| 9 |
|
| 10 |
# MultiTabQA (base-sized model)
|
|
|
|
| 5 |
- multi-table-question-answering
|
| 6 |
license: mit
|
| 7 |
pipeline_tag: table-question-answering
|
| 8 |
+
datasets:
|
| 9 |
+
- vaishali/atis-tableQA
|
| 10 |
---
|
| 11 |
|
| 12 |
# MultiTabQA (base-sized model)
|