Instructions to use hf-tiny-model-private/tiny-random-BertModel 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-BertModel 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-BertModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-BertModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-BertModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a388eae62b847eeab6b7bcd68d8420bc9dda88c4c495b681d623ff67f7da7f40
- Size of remote file:
- 472 kB
- SHA256:
- 35e7ebed853db4f8485ea6df7a84a1010645e81bb7a24c783dbe803cf2d6d09c
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