Instructions to use michaelfeil/Qwen3-Reranker-4B-seq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use michaelfeil/Qwen3-Reranker-4B-seq with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="michaelfeil/Qwen3-Reranker-4B-seq")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("michaelfeil/Qwen3-Reranker-4B-seq") model = AutoModelForSequenceClassification.from_pretrained("michaelfeil/Qwen3-Reranker-4B-seq", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from michaelfeil/Qwen3-Reranker-4B-seq: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/michaelfeil/Qwen3-Reranker-4B-seq/resolve/refs%2Fpr%2F2/tokenizer.json
- Command line
-
hf download hf://michaelfeil/Qwen3-Reranker-4B-seq@refs/pr/2/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/michaelfeil/Qwen3-Reranker-4B-seq/resolve/refs%2Fpr%2F2/tokenizer.json
11.4 MB
- Xet hash:
- 6aec39639a0a2d1ca966356b8c2b8426a484f80ff80731f44fa8482040713bdf
- Size of remote file:
- 11.4 MB
- SHA256:
- aeb13307a71acd8fe81861d94ad54ab689df773318809eed3cbe794b4492dae4
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