Instructions to use badalsahani/oneAPI_roberta_QA_Model_kaggle_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use badalsahani/oneAPI_roberta_QA_Model_kaggle_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="badalsahani/oneAPI_roberta_QA_Model_kaggle_2")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("badalsahani/oneAPI_roberta_QA_Model_kaggle_2") model = AutoModelForQuestionAnswering.from_pretrained("badalsahani/oneAPI_roberta_QA_Model_kaggle_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from badalsahani/oneAPI_roberta_QA_Model_kaggle_2: direct link, hf CLI and curl.
- Browser
- Download file 2.11 MB
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https://huggingface.co/badalsahani/oneAPI_roberta_QA_Model_kaggle_2/resolve/main/tokenizer.json
- Command line
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hf download hf://badalsahani/oneAPI_roberta_QA_Model_kaggle_2/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/badalsahani/oneAPI_roberta_QA_Model_kaggle_2/resolve/main/tokenizer.json
2.11 MB
File too large to display, you can check the raw version instead.