Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use Erfan2001/multilingual_tokenized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Erfan2001/multilingual_tokenized with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Erfan2001/multilingual_tokenized")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Erfan2001/multilingual_tokenized") model = AutoModelForSequenceClassification.from_pretrained("Erfan2001/multilingual_tokenized", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 725149d6e9e6374c614f16b81d4edb877805b4c6ca3a531720a697b8522339c8
- Size of remote file:
- 3.9 kB
- SHA256:
- d4f9d17ec288485944c3330067ebde5d15c9a83cc92152b17f60aa5af677285a
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