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:
- d099f5adf85cbfd0e93494b3a00ac46cb4a99ce3c03824aa3644e2663b47be0f
- Size of remote file:
- 336 kB
- SHA256:
- 4159666ea5174e0cadc33fb391212c790b566009a0895e92214a854eaa99caf8
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