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, dtype="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:
- 0aa9ad6df91c48deb92e05d79e0c20dcc5201d44fb97e1fc075f459e54fe0fd5
- Size of remote file:
- 562 MB
- SHA256:
- 318b11c3ce6d8d34e5034d001166a857934c0811c4fc5fb4a40328477ccaaaf9
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