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:
- f538d63bca5725df0a16beb065b69f77437c73cafbd2918ecc7b6eada8581996
- Size of remote file:
- 10.6 kB
- SHA256:
- 026538e139cfbacd1f794b0198531f98129c67c516d8ca30cffc15fcc231b627
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