Instructions to use Forturne/table_qa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Forturne/table_qa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Forturne/table_qa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Forturne/table_qa") model = AutoModelForQuestionAnswering.from_pretrained("Forturne/table_qa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f659b25f1683484dfb6e372e48024f2060f857a4cdbf07f6fc19d7718c37d756
- Size of remote file:
- 1.34 GB
- SHA256:
- fab5a734a1881220fc78e803fb421704c1b9b727769a340b69ffd0db419abcd0
路
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