Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use somosnlp-hackathon-2022/class-poems-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use somosnlp-hackathon-2022/class-poems-es with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="somosnlp-hackathon-2022/class-poems-es")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("somosnlp-hackathon-2022/class-poems-es") model = AutoModelForSequenceClassification.from_pretrained("somosnlp-hackathon-2022/class-poems-es") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1462961444837a48513c656bd18e8a50879f950923bfc2cf1b738ceebdd9e85b
- Size of remote file:
- 3.06 kB
- SHA256:
- a03e08d192dab7665112fa3c252121aa07f649da191015f0b1dcb941ec8d66e5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.