Instructions to use PlanTL-GOB-ES/bsc-bio-ehr-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PlanTL-GOB-ES/bsc-bio-ehr-es with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="PlanTL-GOB-ES/bsc-bio-ehr-es")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("PlanTL-GOB-ES/bsc-bio-ehr-es") model = AutoModelForMaskedLM.from_pretrained("PlanTL-GOB-ES/bsc-bio-ehr-es", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download process.log from PlanTL-GOB-ES/bsc-bio-ehr-es: direct link, hf CLI and curl.
- Browser
- Download file 775 Bytes
-
https://huggingface.co/PlanTL-GOB-ES/bsc-bio-ehr-es/resolve/main/process.log
- Command line
-
hf download hf://PlanTL-GOB-ES/bsc-bio-ehr-es/process.log
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curl -L -o process.log https://huggingface.co/PlanTL-GOB-ES/bsc-bio-ehr-es/resolve/main/process.log
775 Bytes
| Executing train_tokenizer.py | |
| ------------------------------ | |
| training bbpe tokenizer | |
| Initialize an empty tokenizer | |
| training | |
| saving model tokenizer to /home/shared/dt01/temutauro/ccasimiro/corpus-utils-lm/output/model-ready_output/bio-clinical-vocab-50262-2021-12-07-1604-d1d3-849e/train_tokenizer_output/train-tokenizer-2021-12-07-1625-d1d3-74b8 | |
| saving pretrained to /home/shared/dt01/temutauro/ccasimiro/corpus-utils-lm/output/model-ready_output/bio-clinical-vocab-50262-2021-12-07-1604-d1d3-849e/train_tokenizer_output/train-tokenizer-2021-12-07-1625-d1d3-74b8 | |
| saving config to /home/shared/dt01/temutauro/ccasimiro/corpus-utils-lm/output/model-ready_output/bio-clinical-vocab-50262-2021-12-07-1604-d1d3-849e/train_tokenizer_output/train-tokenizer-2021-12-07-1625-d1d3-74b8 | |