Text Classification
Transformers
Safetensors
modernbert
Generated from Trainer
text-embeddings-inference
Instructions to use harun27/multilabel_paragraph with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harun27/multilabel_paragraph with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="harun27/multilabel_paragraph")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("harun27/multilabel_paragraph") model = AutoModelForSequenceClassification.from_pretrained("harun27/multilabel_paragraph", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4bf6be757dd1217c73133c4e452c878069531241b29806b0ba0a95d0d6ba3640
- Size of remote file:
- 5.37 kB
- SHA256:
- 527e0481d4445b59c1258501668860c01cba05e5331465431997e40803719708
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