Text Classification
Transformers
Safetensors
Arabic
xlm-roberta
arabic
iraqi-dialect
msa
message-classification
fine-tuned
Eval Results (legacy)
text-embeddings-inference
Instructions to use ahmedmajid92/Arabic_MI_Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ahmedmajid92/Arabic_MI_Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ahmedmajid92/Arabic_MI_Classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ahmedmajid92/Arabic_MI_Classifier") model = AutoModelForSequenceClassification.from_pretrained("ahmedmajid92/Arabic_MI_Classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload requirements.txt
Browse files- requirements.txt +6 -0
requirements.txt
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torch>=1.9.0
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transformers>=4.21.0
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datasets>=2.0.0
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gradio>=3.0.0
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numpy>=1.21.0
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huggingface-hub>=0.10.0
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