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:
- b1fd7d9971c0482404b2cccf7153abd8e2c756ebeaf260f8bbbd8cfdc8ea6fc0
- Size of remote file:
- 361 kB
- SHA256:
- b9473ef24f7aa319a9f97a15bd4fda43ae16c9481cb0374deb167398b0e1b860
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