Instructions to use Mardiyyah/tapt_base_LR-2e-05 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mardiyyah/tapt_base_LR-2e-05 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Mardiyyah/tapt_base_LR-2e-05")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Mardiyyah/tapt_base_LR-2e-05") model = AutoModelForMaskedLM.from_pretrained("Mardiyyah/tapt_base_LR-2e-05") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f9932e10e8bc9d82bb770a369e422e97ac92d8cb19594e396f4adb2e5adfbad5
- Size of remote file:
- 166 MB
- SHA256:
- 8b508aa2ac27dee90349dc41cdca5b14d7ba743ef625f28ce4936864ee286028
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