Instructions to use hf-internal-testing/tiny-random-rembert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-rembert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-rembert")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-rembert") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-rembert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8edc9c831360af37884b1db3ad8631f90af004de781d3013494bd22730ff8854
- Size of remote file:
- 33.6 MB
- SHA256:
- 0b684bfd41f7d43cb1588263be82218e11331c9aa0aee602c2497be9e81b8788
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