Instructions to use Mesay/Odio-BERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mesay/Odio-BERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mesay/Odio-BERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Mesay/Odio-BERT") model = AutoModelForSequenceClassification.from_pretrained("Mesay/Odio-BERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1b0a74d24983e4869dad3a4e6afb17907f2b4ed2e19bea9b950a95f905371e1c
- Size of remote file:
- 3.25 kB
- SHA256:
- 3ae8912927f67a7a2409fa196bc5937835a601df0acdaec5649845cf6e9d2231
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