Instructions to use hf-tiny-model-private/tiny-random-FunnelForQuestionAnswering 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-FunnelForQuestionAnswering 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-FunnelForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-FunnelForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-FunnelForQuestionAnswering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a15de06ac9e5ba917c51690e64a8920f53bf20280d19e0e68f0dda3144645624
- Size of remote file:
- 337 kB
- SHA256:
- 2970ab29c699ac2142bb6705ccc2c02e6e5e6a44eb3df28370e4ecf0830a2d54
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