Instructions to use hf-internal-testing/tiny-random-FunnelModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-FunnelModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-FunnelModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-FunnelModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-FunnelModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1d15b062e5d19b8f85e94e04b525316aec5d11838a074f5d8f4d1b2626941565
- Size of remote file:
- 416 kB
- SHA256:
- 298bd054c40a3503eb4c0333ff880dfe735a79143dfa90791cc7353b8a08a1d7
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