Instructions to use hf-internal-testing/tiny-random-FunnelBaseModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-FunnelBaseModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-FunnelBaseModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-FunnelBaseModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-FunnelBaseModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e9b07382f0b781ad532ef957e7e9f57b0e5c2a1654f806264bea5ede0cc86389
- Size of remote file:
- 361 kB
- SHA256:
- 1ed2319809db639b5889857b0d76854305cf5c285114e2f065afbcc69c624c9d
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