Instructions to use rizvi-rahil786/t5-small-equadorEarthquake with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rizvi-rahil786/t5-small-equadorEarthquake with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rizvi-rahil786/t5-small-equadorEarthquake")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rizvi-rahil786/t5-small-equadorEarthquake") model = AutoModelForSequenceClassification.from_pretrained("rizvi-rahil786/t5-small-equadorEarthquake") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c76a00e9c7fceff227884a0ce9590b0d01ae63bb93adbce3f754fd499bed93a0
- Size of remote file:
- 243 MB
- SHA256:
- 59ecf961871a95fe6d831ca9713be9fbb7b823e7c325a82aa967ebb727ea8f07
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