Instructions to use adriansanz/rerank_v5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adriansanz/rerank_v5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="adriansanz/rerank_v5")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("adriansanz/rerank_v5") model = AutoModelForSequenceClassification.from_pretrained("adriansanz/rerank_v5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f5d73ee280a90b3aaaf03d498bf5393d9404e30ac3440df9dad2eebd4ecbc8c9
- Size of remote file:
- 17.1 MB
- SHA256:
- 4a8d0b7573869188be52cca17a27a84f3cfbc0a5536c28ee1eca82903e8c68c6
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