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:
- 1355b390ff4270967c2b3816c65e0ec0fa1f06bb9b1f212e0f966b1b12618c9c
- Size of remote file:
- 383 kB
- SHA256:
- b2461152841921577d15c66a0931535c41648f4692f6238e3d7ef0f7631bcd2e
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