Instructions to use Mardiyyah/TAPT_data-V2_Bioformer-16L_LR-0.0005 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mardiyyah/TAPT_data-V2_Bioformer-16L_LR-0.0005 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Mardiyyah/TAPT_data-V2_Bioformer-16L_LR-0.0005")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Mardiyyah/TAPT_data-V2_Bioformer-16L_LR-0.0005") model = AutoModelForMaskedLM.from_pretrained("Mardiyyah/TAPT_data-V2_Bioformer-16L_LR-0.0005") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eeb3af45eaee2e49b02827445f159d74d72ee93cff73b13d35390763df58775f
- Size of remote file:
- 166 MB
- SHA256:
- af4d5cf55efdac5d5caa5620ac829ecf2a4906a99ce4857d11657f7dda3bd6d1
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