Instructions to use ltmai/morgan-embed-bio-clinical-bert-ddi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ltmai/morgan-embed-bio-clinical-bert-ddi with Transformers:
# Load model directly from transformers import AutoTokenizer, BioClinicalBertClassification tokenizer = AutoTokenizer.from_pretrained("ltmai/morgan-embed-bio-clinical-bert-ddi") model = BioClinicalBertClassification.from_pretrained("ltmai/morgan-embed-bio-clinical-bert-ddi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
morgan-embed-bio-clinical-bert-ddi
This model is a fine-tuned version of on an unknown dataset.
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.000628
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1
- Datasets 2.13.1
- Tokenizers 0.13.3
- Downloads last month
- 7
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support