Instructions to use shawnw3i/Qwen3-Embedding-4B-ONNX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shawnw3i/Qwen3-Embedding-4B-ONNX with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="shawnw3i/Qwen3-Embedding-4B-ONNX")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("shawnw3i/Qwen3-Embedding-4B-ONNX") model = AutoModelForCausalLM.from_pretrained("shawnw3i/Qwen3-Embedding-4B-ONNX", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Fix export error
Browse files- config.json +1 -1
- model.onnx +2 -2
- model.onnx_data +2 -2
- tokenizer.json +2 -2
config.json
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"rope_theta": 1000000,
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"sliding_window": null,
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"tie_word_embeddings": true,
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"torch_dtype": "
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"transformers_version": "4.52.4",
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"use_cache": false,
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"use_sliding_window": false,
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"rope_theta": 1000000,
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"sliding_window": null,
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"tie_word_embeddings": true,
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"torch_dtype": "float16",
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"transformers_version": "4.52.4",
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"use_cache": false,
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"use_sliding_window": false,
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model.onnx
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size 1581043
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model.onnx_data
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size 8043530240
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tokenizer.json
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size 11422947
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