Text Classification
Transformers
Safetensors
bert
multilabel
history
holocaust
heritage
text-embeddings-inference
Instructions to use ufal/labse-malach-multilabel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ufal/labse-malach-multilabel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ufal/labse-malach-multilabel")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ufal/labse-malach-multilabel") model = AutoModelForSequenceClassification.from_pretrained("ufal/labse-malach-multilabel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1924474b8137e751a3e86b04d267b75ec3a089b344ae55e29be734a03942edc9
- Size of remote file:
- 13.6 MB
- SHA256:
- 7f4f8cebf07aea8174f1e075b4985c42f4354e6d81f9c5a59aef3ba6849c138a
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