Instructions to use dengcao/Qwen3-Reranker-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dengcao/Qwen3-Reranker-4B with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("dengcao/Qwen3-Reranker-4B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| # SPDX-License-Identifier: Apache-2.0 | |
| # SPDX-FileCopyrightText: Copyright contributors to the vLLM project | |
| from .interfaces import (HasInnerState, SupportsLoRA, SupportsMultiModal, | |
| SupportsPP, SupportsV0Only, has_inner_state, | |
| supports_lora, supports_multimodal, supports_pp, | |
| supports_v0_only) | |
| from .interfaces_base import (VllmModelForPooling, VllmModelForTextGeneration, | |
| is_pooling_model, is_text_generation_model) | |
| from .registry import ModelRegistry | |
| __all__ = [ | |
| "ModelRegistry", | |
| "VllmModelForPooling", | |
| "is_pooling_model", | |
| "VllmModelForTextGeneration", | |
| "is_text_generation_model", | |
| "HasInnerState", | |
| "has_inner_state", | |
| "SupportsLoRA", | |
| "supports_lora", | |
| "SupportsMultiModal", | |
| "supports_multimodal", | |
| "SupportsPP", | |
| "supports_pp", | |
| "SupportsV0Only", | |
| "supports_v0_only", | |
| ] | |