Instructions to use hf-tiny-model-private/tiny-random-FunnelModel 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-FunnelModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-FunnelModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-FunnelModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-FunnelModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6e601bf74779b4b6573a0a8d4ed4f19d2029c3be8176dc6bfe6e45298087cc01
- Size of remote file:
- 416 kB
- SHA256:
- d6eb7c8d04164858268cb0494f9b3a11268b894067d7b2cee34df442243f53e4
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