Instructions to use harish/PT-v3-dev-test-all-PreTrain-e5-select with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harish/PT-v3-dev-test-all-PreTrain-e5-select with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="harish/PT-v3-dev-test-all-PreTrain-e5-select")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("harish/PT-v3-dev-test-all-PreTrain-e5-select") model = AutoModelForMaskedLM.from_pretrained("harish/PT-v3-dev-test-all-PreTrain-e5-select") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 362d3e9f22e3b4b0171b2cc1dad53d352d885b5e3c3cde72d2740436e47e5530
- Size of remote file:
- 712 MB
- SHA256:
- 47e4fdbcc6cdded7db7ef4e7f29f1ea44b630cba5082ce39855f0ccbace5517d
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