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