Instructions to use youssefkhalil320/Multilingual-MiniLM-L12-H384-resumesClasssifierV1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use youssefkhalil320/Multilingual-MiniLM-L12-H384-resumesClasssifierV1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="youssefkhalil320/Multilingual-MiniLM-L12-H384-resumesClasssifierV1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("youssefkhalil320/Multilingual-MiniLM-L12-H384-resumesClasssifierV1") model = AutoModelForSequenceClassification.from_pretrained("youssefkhalil320/Multilingual-MiniLM-L12-H384-resumesClasssifierV1", device_map="auto") - Notebooks
- Google Colab
- Kaggle