Instructions to use raphaelsty/model-test-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use raphaelsty/model-test-onnx with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("raphaelsty/model-test-onnx") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Upload README.md with huggingface_hub
Browse files
README.md
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- **Source Model**: [unknown](https://huggingface.co/unknown)
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- **Embedding Dimension**: unknown
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- **Format**: ONNX (FP32)
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## Files
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| File | Description |
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| `model.onnx` | FP32 ONNX model |
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| `tokenizer.json` | Tokenizer configuration |
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| `config_sentence_transformers.json` | Model configuration |
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- **Source Model**: [unknown](https://huggingface.co/unknown)
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- **Embedding Dimension**: unknown
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- **Format**: ONNX (FP32 + INT8)
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## Files
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| File | Description |
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|------|-------------|
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| `model.onnx` | FP32 ONNX model |
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| `model_int8.onnx` | INT8 quantized model (faster) |
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| `tokenizer.json` | Tokenizer configuration |
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| `config_sentence_transformers.json` | Model configuration |
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