Instructions to use deepset/electra-base-squad2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepset/electra-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/electra-base-squad2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("deepset/electra-base-squad2") model = AutoModelForQuestionAnswering.from_pretrained("deepset/electra-base-squad2", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from deepset/electra-base-squad2: direct link, hf CLI and curl.
- Browser
- Download file 200 Bytes
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https://huggingface.co/deepset/electra-base-squad2/resolve/main/tokenizer_config.json
- Command line
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hf download hf://deepset/electra-base-squad2/tokenizer_config.json
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curl -L -o tokenizer_config.json https://huggingface.co/deepset/electra-base-squad2/resolve/main/tokenizer_config.json
200 Bytes
| {"do_lower_case": true, "model_max_length": 512, "special_tokens_map_file": "/home/vaishali/Documents/deepset/electra-english-qa-tutorial_epochs5/special_tokens_map.json", "full_tokenizer_file": null} |