Instructions to use Intel/tiny-random-bert_ipex_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Intel/tiny-random-bert_ipex_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Intel/tiny-random-bert_ipex_model")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Intel/tiny-random-bert_ipex_model") model = AutoModelForQuestionAnswering.from_pretrained("Intel/tiny-random-bert_ipex_model") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -14,4 +14,4 @@ model = IPEXModelForQuestionAnswering.from_pretrained("Intel/tiny-random-bert")
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model.push_to_hub("Intel/tiny-random-bert_ipex_model")
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```
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This is useful for functional testing (not quality generation, since its weights are random)
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model.push_to_hub("Intel/tiny-random-bert_ipex_model")
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```
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This is useful for functional testing (not quality generation, since its weights are random) on [optimum-intel](https://github.com/huggingface/optimum-intel/blob/main/tests/ipex/utils_tests.py)
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