Question Answering
Transformers
PyTorch
Safetensors
English
deberta-v2
deberta
deberta-v3
squad
squad_v2
mrqa
synQA
adversarial_qa
Eval Results (legacy)
Instructions to use sjrhuschlee/deberta-v3-base-squad2-ext-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sjrhuschlee/deberta-v3-base-squad2-ext-v1 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="sjrhuschlee/deberta-v3-base-squad2-ext-v1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("sjrhuschlee/deberta-v3-base-squad2-ext-v1") model = AutoModelForQuestionAnswering.from_pretrained("sjrhuschlee/deberta-v3-base-squad2-ext-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from sjrhuschlee/deberta-v3-base-squad2-ext-v1: direct link, hf CLI and curl.
- Browser
- Download file 8.66 MB
-
https://huggingface.co/sjrhuschlee/deberta-v3-base-squad2-ext-v1/resolve/main/tokenizer.json
- Command line
-
hf download hf://sjrhuschlee/deberta-v3-base-squad2-ext-v1/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/sjrhuschlee/deberta-v3-base-squad2-ext-v1/resolve/main/tokenizer.json
8.66 MB
File too large to display, you can check the raw version instead.