Instructions to use Vlasta/randomWeightsBert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Vlasta/randomWeightsBert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Vlasta/randomWeightsBert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Vlasta/randomWeightsBert") model = AutoModelForMaskedLM.from_pretrained("Vlasta/randomWeightsBert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 598e7206592f1e9e9150be155798dca8bc0702825d6278957f8b82068ae5b2d2
- Size of remote file:
- 357 MB
- SHA256:
- b0c0b262f73f243fefcc22265544105d47644501ee090de13195f1ae029e27cc
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