Text Classification
Transformers
PyTorch
Safetensors
Spanish
roberta
biomedical
clinical
eHR
spanish
roberta-large-bne
Eval Results (legacy)
text-embeddings-inference
Instructions to use IIC/roberta-large-bne-cantemist with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IIC/roberta-large-bne-cantemist with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="IIC/roberta-large-bne-cantemist")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("IIC/roberta-large-bne-cantemist") model = AutoModelForSequenceClassification.from_pretrained("IIC/roberta-large-bne-cantemist", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6191a08efbb21c9d9c31d8b3e11fd1f7c71f97c6dbf66d24659618595311f184
- Size of remote file:
- 1.42 GB
- SHA256:
- a4f7c45cb12cff8f4fc6380a886c236f84c07d157c459b61f787c18d34941f41
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