Instructions to use Ermira/qa_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ermira/qa_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Ermira/qa_model")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Ermira/qa_model") model = AutoModelForQuestionAnswering.from_pretrained("Ermira/qa_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 91e67ae7b25d3f21dd580fa4c3fb6fa1ec64364c88f03da1750ac7554ef692f9
- Size of remote file:
- 4.86 kB
- SHA256:
- a420a6ac21501bf82c3a4bc5148614022bfa2f4cde4ab1e8bdd817ce07879fc4
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.