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
- Xet hash:
- bc147cb641c943befb5edbf0510f85b895386e32fdc36dc4dbecfad4df384e4a
- Size of remote file:
- 8.04 GB
- SHA256:
- a17a581520e50dca35994bd8ce5f30af2431f718a90a3b8d221e6f8c6a15db35
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