Text Classification
Transformers
PyTorch
ONNX
Safetensors
distilbert
sentiment-analysis
zero-shot-distillation
distillation
zero-shot-classification
debarta-v3
text-embeddings-inference
Instructions to use lxyuan/distilbert-base-multilingual-cased-sentiments-student with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lxyuan/distilbert-base-multilingual-cased-sentiments-student with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lxyuan/distilbert-base-multilingual-cased-sentiments-student")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lxyuan/distilbert-base-multilingual-cased-sentiments-student") model = AutoModelForSequenceClassification.from_pretrained("lxyuan/distilbert-base-multilingual-cased-sentiments-student", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
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