Text Classification
Transformers
PyTorch
roberta
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Carlos31/platzi-distilroberta-base-mrpc-glue-Carlos-Moreno with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Carlos31/platzi-distilroberta-base-mrpc-glue-Carlos-Moreno with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Carlos31/platzi-distilroberta-base-mrpc-glue-Carlos-Moreno")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Carlos31/platzi-distilroberta-base-mrpc-glue-Carlos-Moreno") model = AutoModelForSequenceClassification.from_pretrained("Carlos31/platzi-distilroberta-base-mrpc-glue-Carlos-Moreno", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1 opened over 1 year ago
by
SFconvertbot