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 # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="deepset/roberta-base-squad2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("deepset/roberta-base-squad2") model = AutoModelForQuestionAnswering.from_pretrained("deepset/roberta-base-squad2", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from deepset/roberta-base-squad2: direct link, hf CLI and curl.
- Browser
- Download file 497 MB
-
https://huggingface.co/deepset/roberta-base-squad2/resolve/refs%2Fpr%2F26/tf_model.h5
- Command line
-
hf download hf://deepset/roberta-base-squad2@refs/pr/26/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/deepset/roberta-base-squad2/resolve/refs%2Fpr%2F26/tf_model.h5
497 MB
- Xet hash:
- 72c5aeabc037039b8848af6201312d1b6590711e797f47fb4880cd3b5cc0b149
- Size of remote file:
- 497 MB
- SHA256:
- 9b672dd16f09f6f805d407800278e60217b9d7c040df1dde5098765a40cdc88a
路
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