Instructions to use fklska/cross_encoder_ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fklska/cross_encoder_ft with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="fklska/cross_encoder_ft")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("fklska/cross_encoder_ft") model = AutoModelForSequenceClassification.from_pretrained("fklska/cross_encoder_ft", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0f2f7ac85d34b9e8afdee91567e931ae7b020c351c44cab700730f8f506b8a25
- Size of remote file:
- 5.14 kB
- SHA256:
- 191954197402247712d9fcb8f6dfde4cc2313800baf09b5cc5e57f70a1a3f84e
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