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:
- 23ae48b0593659fa0c7c37508be0ebbe0fe635532e8e214c45b23761db303166
- Size of remote file:
- 115 MB
- SHA256:
- 041ceff1793d6c89e7724e3641019a8e8e2ecd76a41a54892ad494f99c618b35
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