Text Classification
Transformers
PyTorch
Transformers.js
multilingual
reranker
cross-encoder
custom_code
Instructions to use teslov/reranker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use teslov/reranker with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="teslov/reranker", trust_remote_code=True)# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("teslov/reranker", trust_remote_code=True, device_map="auto") - Transformers.js
How to use teslov/reranker with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('text-classification', 'teslov/reranker'); - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fd8b244b613f7189b1547758d849817b284f0f3ae52113a915789f927ee4b164
- Size of remote file:
- 17.1 MB
- SHA256:
- 3a56def25aa40facc030ea8b0b87f3688e4b3c39eb8b45d5702b3a1300fe2a20
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