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README.md
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@@ -93,7 +93,7 @@ The input to the model is called `logits`, and there is one output per label. Ea
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# huggingface.co/sentence-transformers/all-MiniLM-L12-v2
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# or from an ONNX version E.g. huggingface.co/Xenova/all-MiniLM-L12-v2
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print(
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> (1, 384)
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import onnxruntime as ort
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sess = ort.InferenceSession("path_to_model_dot_onnx", providers=['CPUExecutionProvider'])
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outputs = [o.name for o in sess.get_outputs()] # list of labels, in the order of the outputs
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preds_onnx = sess.run(_outputs, {'logits':
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# preds_onnx is a list with 28 entries, one per label,
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# each with a numpy array of shape (1, 2) given the input was a batch of 1
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# huggingface.co/sentence-transformers/all-MiniLM-L12-v2
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# or from an ONNX version E.g. huggingface.co/Xenova/all-MiniLM-L12-v2
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print(embeddings.shape) # E.g. a batch of 1 sentence
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> (1, 384)
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import onnxruntime as ort
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sess = ort.InferenceSession("path_to_model_dot_onnx", providers=['CPUExecutionProvider'])
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outputs = [o.name for o in sess.get_outputs()] # list of labels, in the order of the outputs
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preds_onnx = sess.run(_outputs, {'logits': embeddings})
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# preds_onnx is a list with 28 entries, one per label,
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# each with a numpy array of shape (1, 2) given the input was a batch of 1
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