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:
- 90f9eb32762b7246e0ea7223535475a1ebe44bb82fda6c6cfbfbe33b6a805d1a
- Size of remote file:
- 336 kB
- SHA256:
- 2b842be79549eb5c4d39de564354a7c1615d0c20917d4397619fb82a747cef94
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