Instructions to use TheAIchemist13/span_extraction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TheAIchemist13/span_extraction with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="TheAIchemist13/span_extraction")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("TheAIchemist13/span_extraction") model = AutoModelForQuestionAnswering.from_pretrained("TheAIchemist13/span_extraction") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 99cce2197cd29be96d2cc4a93e372f9d3005c703acd027dadea20ffaf0513a0e
- Size of remote file:
- 436 MB
- SHA256:
- aab9b8e84245c5a544803374767a5a542fdb73da0db63de51c9a27ad37c53558
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.