Instructions to use hf-internal-testing/tiny-random-XLNetForQuestionAnsweringSimple with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-XLNetForQuestionAnsweringSimple 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="hf-internal-testing/tiny-random-XLNetForQuestionAnsweringSimple")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-XLNetForQuestionAnsweringSimple") model = AutoModelForQuestionAnswering.from_pretrained("hf-internal-testing/tiny-random-XLNetForQuestionAnsweringSimple", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-XLNetForQuestionAnsweringSimple: direct link, hf CLI and curl.
- Browser
- Download file 4.38 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-XLNetForQuestionAnsweringSimple/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-XLNetForQuestionAnsweringSimple@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-XLNetForQuestionAnsweringSimple/resolve/refs%2Fpr%2F1/model.safetensors
4.38 MB
- Xet hash:
- 48fa0b3dcf0bab4a915476b82ebfc0843592da4e3f2420185731246feb0aff7d
- Size of remote file:
- 4.38 MB
- SHA256:
- 9b06b3dc10d1923cfbf094123bb6eea8579f60760d2e4e36d56b03bfe6a86310
路
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