Instructions to use Amna100/Augmented-PreTraining-MLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Amna100/Augmented-PreTraining-MLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Amna100/Augmented-PreTraining-MLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Amna100/Augmented-PreTraining-MLM") model = AutoModelForMaskedLM.from_pretrained("Amna100/Augmented-PreTraining-MLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 46d24251492d2a5224e614cc5e57ebdeecb81b549501dce1de6d7fe389107afa
- Size of remote file:
- 5.05 kB
- SHA256:
- baafceb30084ff14a1cc8f8f3463191c89aae654ba475ce1551ffc2499981520
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