Text Classification
Transformers
Safetensors
PyTorch
Arabic
bert
arabic
classification
complaint-classification
telecom
yemeni-arabic
text-embeddings-inference
Instructions to use En-ayman/proplemmodel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use En-ayman/proplemmodel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="En-ayman/proplemmodel")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("En-ayman/proplemmodel") model = AutoModelForSequenceClassification.from_pretrained("En-ayman/proplemmodel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from En-ayman/proplemmodel: direct link, hf CLI and curl.
- Browser
- Download file 2.69 MB
-
https://huggingface.co/En-ayman/proplemmodel/resolve/main/tokenizer.json
- Command line
-
hf download hf://En-ayman/proplemmodel/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/En-ayman/proplemmodel/resolve/main/tokenizer.json
2.69 MB
File too large to display, you can check the raw version instead.