Instructions to use hf-tiny-model-private/tiny-random-OPTForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-OPTForQuestionAnswering with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="hf-tiny-model-private/tiny-random-OPTForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-OPTForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-OPTForQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ec60a74496c260cab8f497457a14472427291d975aec150803119a524914f1a5
- Size of remote file:
- 125 kB
- SHA256:
- 2962e82dc3119b03a383a10eb8425abac087a25bf30ce90db61bf1d8fbad765f
路
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