Instructions to use HydraLM/bge-large-classifier-32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HydraLM/bge-large-classifier-32 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HydraLM/bge-large-classifier-32")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HydraLM/bge-large-classifier-32") model = AutoModelForSequenceClassification.from_pretrained("HydraLM/bge-large-classifier-32") - Notebooks
- Google Colab
- Kaggle
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- 1.52 kB
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- 1.34 GB xet
- 3.96 kB xet