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:
- a77008c14a60a74515fab4665cfdc4d9fc375b8f349a7ae2e6de50afd9300e35
- Size of remote file:
- 18.3 MB
- SHA256:
- 6a1e439ef72d2889d50ec92b310930aac1c3194cebd94a58bcad28880a1c407d
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