Instructions to use ashraq/bert-random-weights with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ashraq/bert-random-weights with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ashraq/bert-random-weights")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ashraq/bert-random-weights") model = AutoModelForMaskedLM.from_pretrained("ashraq/bert-random-weights", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b4e63f80c05c4365682dd042cafddc0528e61184e0fdfc8b87e5b9d4002b490f
- Size of remote file:
- 1.89 GB
- SHA256:
- 95d7329e9cb82953c363b765be1172658d5b0b67e16260c29c66492d21b6124b
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