Instructions to use Amna100/PreTraining-MLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Amna100/PreTraining-MLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Amna100/PreTraining-MLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Amna100/PreTraining-MLM") model = AutoModelForMaskedLM.from_pretrained("Amna100/PreTraining-MLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c3e125ddf8abd2dd4f37a7803daa0d17f8c8512ad7fe65107a52251044695f28
- Size of remote file:
- 4.73 kB
- SHA256:
- 31fe7efed097d2af98a110af858bb3271557f8ea95f54ddc4fd4b1a0f7485b8d
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