Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use fredymad/robertuito_Pfinal with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fredymad/robertuito_Pfinal with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="fredymad/robertuito_Pfinal")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("fredymad/robertuito_Pfinal") model = AutoModelForSequenceClassification.from_pretrained("fredymad/robertuito_Pfinal", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f53153d5a7d900a7d359b2d4645509299fcc1764cfb90c8843ed6a0bea6f8116
- Size of remote file:
- 3.58 kB
- SHA256:
- d96519fa9667e987960ac42c9d58a39527157ebdc08f60d434b3492573a0e970
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