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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7f98b31a296ca846d2c7f714eec91a5f983cd3791055432c136574bbd6c656aa
- Size of remote file:
- 298 kB
- SHA256:
- e87db861666644e59d4cad1a98238676650e01e0a5fda901d218ffff5dc5b397
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