Instructions to use Mardiyyah/TAPT_data-V2_Bioformer-16L_LR-0.0001 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-0.0001 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-0.0001")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Mardiyyah/TAPT_data-V2_Bioformer-16L_LR-0.0001") model = AutoModelForMaskedLM.from_pretrained("Mardiyyah/TAPT_data-V2_Bioformer-16L_LR-0.0001") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ccaf6d19cf15d97cadd6117474d7b280116d34b4fc789da8e3a35b83a503caf6
- Size of remote file:
- 166 MB
- SHA256:
- 6cc50c7f427d9dd3bed1e21f1e97fa960ae01abb451a74d8fae406988cbe5b0b
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