Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use hebashakeel/bert-wellness-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hebashakeel/bert-wellness-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hebashakeel/bert-wellness-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hebashakeel/bert-wellness-classifier") model = AutoModelForSequenceClassification.from_pretrained("hebashakeel/bert-wellness-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from hebashakeel/bert-wellness-classifier: direct link, hf CLI and curl.
- Browser
- Download file 5.24 kB
-
https://huggingface.co/hebashakeel/bert-wellness-classifier/resolve/main/training_args.bin
- Command line
-
hf download hf://hebashakeel/bert-wellness-classifier/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/hebashakeel/bert-wellness-classifier/resolve/main/training_args.bin
5.24 kB
- Xet hash:
- 81f6c34b337c7746e4fdb6242458147d863c865362d7e63ad176caa817840830
- Size of remote file:
- 5.24 kB
- SHA256:
- ecd622812a5272206544919535b0084a20180235c837901e492a64deb534c756
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