Question Answering
Transformers
PyTorch
TensorFlow
JAX
Rust
Safetensors
English
roberta
Eval Results (legacy)
Instructions to use deepset/roberta-base-squad2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepset/roberta-base-squad2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="deepset/roberta-base-squad2")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("deepset/roberta-base-squad2") model = AutoModelForQuestionAnswering.from_pretrained("deepset/roberta-base-squad2") - Inference
- Notebooks
- Google Colab
- Kaggle
Add TF weights
#3
by joaogante - opened
Validated by the pt_to_tf CLI. Max crossload output difference=2.337e-05; Max converted output difference=2.337e-05.
Hi again 👋
My apologies -- our automatic conversion tool was missing the conversion of some model heads, and this was one of the incomplete conversions. We also added much stricter equivalence tests (https://github.com/huggingface/transformers/pull/17588), to ensure TF users enjoy the exact same model experience as PT users.
timomo changed pull request status to merged