Token Classification
Transformers
PyTorch
Safetensors
Spanish
roberta
text-classification
biomedical
clinical
spanish
bsc-bio-ehr-es
Eval Results (legacy)
Instructions to use IIC/bsc-bio-ehr-es-socialdisner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IIC/bsc-bio-ehr-es-socialdisner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="IIC/bsc-bio-ehr-es-socialdisner")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("IIC/bsc-bio-ehr-es-socialdisner") model = AutoModelForSequenceClassification.from_pretrained("IIC/bsc-bio-ehr-es-socialdisner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from IIC/bsc-bio-ehr-es-socialdisner: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/IIC/bsc-bio-ehr-es-socialdisner/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://IIC/bsc-bio-ehr-es-socialdisner/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/IIC/bsc-bio-ehr-es-socialdisner/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- 9843a3b3fc91aabcaf53d3c001ce241f46f9106eaa0045b58e75b93f3c3274eb
- Size of remote file:
- 499 MB
- SHA256:
- 635e85e92760566e6451dbbb11c9a0794b284b2b5a399e1942cc9c13c7e408d4
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