Instructions to use hf-tiny-model-private/tiny-random-RemBertModel 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-RemBertModel 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-RemBertModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-RemBertModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-RemBertModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aa097f3c07ba869bf6a1f544e808af19412a21ad40b130c3782cb1be12fafcde
- Size of remote file:
- 18.3 MB
- SHA256:
- 75125ae1ffeaabcc43fdc577d4ed22f800548a7a2a93c0e36fa7fcf163350b60
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