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udpate
Signed-off-by: Jael Gu <mengjia.gu@zilliz.com>
main
2 changed files with
8 additions and
16 deletions
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README.md
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BIN
result.png
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@ -19,27 +19,19 @@ Use the pre-trained model "microsoft/unixcoder-base" |
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to generate text embeddings for given |
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text description "return max value" and code "def max(a,b): if a>b: return a else return b". |
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*Write the pipeline*: |
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*Write a pipeline with explicit inputs/outputs name specifications:* |
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```python |
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import towhee |
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from towhee.dc2 import pipe, ops, DataCollection |
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( |
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towhee.dc(['find max value', 'def max(a,b): if a>b: return a else return b']) |
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.code_search.unixcoder(model_name='microsoft/unixcoder-base') |
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p = ( |
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pipe.input('text') |
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.map('text', 'embedding', ops.code_search.unixcoder()) |
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.output('text', 'embedding') |
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) |
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``` |
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*Write a same pipeline with explicit inputs/outputs name specifications:* |
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```python |
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import towhee |
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( |
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towhee.dc['text'](['return max value', 'def max(a,b): if a>b: return a else return b']) |
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.code_search.unixcoder['text', 'embedding']() |
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.show() |
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) |
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DataCollection(p('find max value')).show() |
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DataCollection(p('def max(a,b): if a>b: return a else return b')).show() |
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``` |
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<img src="./result.png" width="800px"/> |
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Width:
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Height:
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Size: 13 KiB
Width:
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Height:
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Size: 14 KiB
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