Text Classification
Transformers
PyTorch
ONNX
English
bert
text-generation
text-embeddings-inference
Instructions to use MattStammers/Covid19_Text_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MattStammers/Covid19_Text_Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MattStammers/Covid19_Text_Model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MattStammers/Covid19_Text_Model") model = AutoModelForSequenceClassification.from_pretrained("MattStammers/Covid19_Text_Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7563ac94115cfa3ca72d9324b1bed0dae26508dbccb93cfc890fd5eaea48e726
- Size of remote file:
- 4.03 kB
- SHA256:
- a376d2cae4c0f66886c32d18817d01dd4d18dc16f5450867a1fa144d623eb3b5
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