Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use cwchang/text-classification-model-multilingual with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cwchang/text-classification-model-multilingual with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cwchang/text-classification-model-multilingual")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cwchang/text-classification-model-multilingual") model = AutoModelForSequenceClassification.from_pretrained("cwchang/text-classification-model-multilingual") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ec592fd1bd9012a1805cca600ca8dc62c1eb98bce7f59f7f070af76afe169cae
- Size of remote file:
- 4.79 kB
- SHA256:
- 8a4192f9304a4e3738d0be872d5509fcf84dc9d71d6e7502757dfe464b4e24eb
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