Text Classification
Transformers
PyTorch
Safetensors
Transformers.js
English
bert
feature-extraction
reranker
cross-encoder
custom_code
text-embeddings-inference
Instructions to use llmware/jina-reranker-v1-tiny-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use llmware/jina-reranker-v1-tiny-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="llmware/jina-reranker-v1-tiny-en", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("llmware/jina-reranker-v1-tiny-en", trust_remote_code=True) model = AutoModel.from_pretrained("llmware/jina-reranker-v1-tiny-en", trust_remote_code=True) - Transformers.js
How to use llmware/jina-reranker-v1-tiny-en with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('text-classification', 'llmware/jina-reranker-v1-tiny-en'); - Notebooks
- Google Colab
- Kaggle
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