Instructions to use hf-internal-testing/tiny-random-OPTForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-OPTForQuestionAnswering with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="hf-internal-testing/tiny-random-OPTForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-OPTForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-internal-testing/tiny-random-OPTForQuestionAnswering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 75e769420e9bec96b355c9580c542a2a2393760a33d4880a95b954ca948151a2
- Size of remote file:
- 3.28 MB
- SHA256:
- d92537c1455d5d4ac08becfddf09c17a919f32d33aa5209c9aea9081c85fcd50
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