Instructions to use hf-tiny-model-private/tiny-random-FunnelBaseModel 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-FunnelBaseModel 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-FunnelBaseModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-FunnelBaseModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-FunnelBaseModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3b6536e11a1633f02124a3052d7db86dbf33960c4dd676832765b6b8cc90735c
- Size of remote file:
- 280 kB
- SHA256:
- 46596acb7d57990af58f6cdd3cc961a7a9b2fd0fad1f4d97c64346d0ceae4367
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