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 # 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="Intel/tiny-random-bert_ipex_model")# pip install -U transformers accelerate # 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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Intel/tiny-random-bert_ipex_model: direct link, hf CLI and curl.
- Browser
- Download file 377 kB
-
https://huggingface.co/Intel/tiny-random-bert_ipex_model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Intel/tiny-random-bert_ipex_model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Intel/tiny-random-bert_ipex_model/resolve/main/pytorch_model.bin
377 kB
- Xet hash:
- e7de630d317ce542e8c93c508843284c4d4e8364c950e48af643a7328cddb611
- Size of remote file:
- 377 kB
- SHA256:
- d6cb7cc3120628d9056114fb09b2ec90ddd29e68ab763d4ab38fb3bd4daa5cc4
路
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