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Signed-off-by: Jael Gu <mengjia.gu@zilliz.com>
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Jael Gu 2 years ago
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      README.md

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README.md

@ -352,14 +352,6 @@ and then return text embedding in ndarray.
If data is string, the operator returns embedding(s) in ndarray. If data is string, the operator returns embedding(s) in ndarray.
If data is a list, the operator returns embedding(s) in a list. If data is a list, the operator returns embedding(s) in a list.
**Returns**:
*numpy.ndarray*
​ The text embedding extracted by model.
<br /> <br />
***save_model(format='pytorch', path='default')*** ***save_model(format='pytorch', path='default')***
@ -408,6 +400,16 @@ print(f'Onnx-support/Total Models: {len(onnx_list)}/{len(full_list)}')
2022-12-13 16:25:15,916 - 140704500614336 - auto_transformers.py-auto_transformers:68 - WARNING: The operator is initialized without specified model. 2022-12-13 16:25:15,916 - 140704500614336 - auto_transformers.py-auto_transformers:68 - WARNING: The operator is initialized without specified model.
Onnx-support/Total Models: 111/126 Onnx-support/Total Models: 111/126
<br />
**Returns**:
*numpy.ndarray or list*
​ The text embedding (or token embeddings) extracted by model.
<br />
## Fine-tune ## Fine-tune
### Requirement ### Requirement
If you want to train this operator, besides dependency in requirements.txt, you need install these dependencies. If you want to train this operator, besides dependency in requirements.txt, you need install these dependencies.

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