Instructions to use vantan/Cross-Encoder-LLamaIndex with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vantan/Cross-Encoder-LLamaIndex with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="vantan/Cross-Encoder-LLamaIndex")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("vantan/Cross-Encoder-LLamaIndex") model = AutoModelForSequenceClassification.from_pretrained("vantan/Cross-Encoder-LLamaIndex", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 554581037924fb6b499d188efdcd24b843311df33b241de4c53d4bcead2ec1e8
- Size of remote file:
- 133 MB
- SHA256:
- bf5dbf94b73975ccbb855cb897f56efc17f207da705596ca9466f435849e0754
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