Instructions to use hf-internal-testing/tiny-random-RemBertModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-RemBertModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-RemBertModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-RemBertModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-RemBertModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5c2af46499ea81d0b87a73985b619a84430fc62aa14518e3d4bf336153ab134e
- Size of remote file:
- 18.2 MB
- SHA256:
- dd502a5b90064e2b5785a0614d2215305b05b25a6c3cfc280a47388e8e5736d5
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