Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use fathyshalaby/emailclassifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fathyshalaby/emailclassifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="fathyshalaby/emailclassifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("fathyshalaby/emailclassifier") model = AutoModelForSequenceClassification.from_pretrained("fathyshalaby/emailclassifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from fathyshalaby/emailclassifier: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/fathyshalaby/emailclassifier/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://fathyshalaby/emailclassifier@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/fathyshalaby/emailclassifier/resolve/refs%2Fpr%2F1/pytorch_model.bin
268 MB
- Xet hash:
- 4edbb453d08127ce306f7b61dad874a5171afa021da0fe6db4acb11913e735ca
- Size of remote file:
- 268 MB
- SHA256:
- 5d9a0f384f4e49e4a2495454b2b7f35fefa3935b55e0b0c71449111171d3677d
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