Instructions to use shubov/omop_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shubov/omop_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="shubov/omop_bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("shubov/omop_bert") model = AutoModelForMaskedLM.from_pretrained("shubov/omop_bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Model save
Browse files- README.md +1 -1
- model.safetensors +1 -1
- training_args.bin +1 -1
README.md
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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### Training results
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- training_steps: 3
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### Training results
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model.safetensors
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training_args.bin
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