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Download Pre-trained Models

🛠️ Hugging Face to ONNX Converter:

These Python scripts convert Hugging Face models into the ONNX format for optimized inference.

These scripts handle two primary use cases:

  1. Feature extraction models (e.g., sentence-transformers).
  2. Token classification models (e.g., Named Entity Recognition - NER).

It automatically downloads the model and organizes the exported files in a structured subdirectory.

Requirements

Before running the script, make sure you have the following Python packages installed:

pip install torch transformers onnx onnxruntime optimum

Examples

python3 models/hf_model_to_onnx.py -m="dbmdz/bert-large-cased-finetuned-conll03-english" -o="bert-large-cased-finetuned-conll03-english"
python3 models/hf_model_to_onnx.py -m="sentence-transformers/all-MiniLM-L6-v2" -o="sentence-transformers/all-MiniLM-L6-v2"

Output

./models/
    ├── hf_extract_model.py
    ├── hf_model_to_onnx.py
    ├── sentence-transformers/all-MiniLM-L6-v2/ 
    │    ├── model.onnx (via optimum)
    │    └── tokenizer/ 
    └── dslim/bert-base-NER/  
        ├── model.onnx  
        ├── label_map.json  
        └── tokenizer/