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Upload h2oai_pipeline.py

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  1. h2oai_pipeline.py +42 -0
h2oai_pipeline.py ADDED
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+ from transformers import TextGenerationPipeline
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+ from transformers.pipelines.text_generation import ReturnType
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+
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+ STYLE = "<|prompt|>{instruction}</s><|answer|>"
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+
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+
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+ class H2OTextGenerationPipeline(TextGenerationPipeline):
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+ def __init__(self, *args, **kwargs):
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+ super().__init__(*args, **kwargs)
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+ self.prompt = STYLE
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+
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+ def preprocess(
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+ self, prompt_text, prefix="", handle_long_generation=None, **generate_kwargs
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+ ):
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+ prompt_text = self.prompt.format(instruction=prompt_text)
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+ return super().preprocess(
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+ prompt_text,
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+ prefix=prefix,
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+ handle_long_generation=handle_long_generation,
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+ **generate_kwargs,
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+ )
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+
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+ def postprocess(
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+ self,
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+ model_outputs,
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+ return_type=ReturnType.FULL_TEXT,
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+ clean_up_tokenization_spaces=True,
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+ ):
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+ records = super().postprocess(
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+ model_outputs,
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+ return_type=return_type,
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+ clean_up_tokenization_spaces=clean_up_tokenization_spaces,
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+ )
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+ for rec in records:
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+ rec["generated_text"] = (
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+ rec["generated_text"]
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+ .split("<|answer|>")[1]
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+ .strip()
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+ .split("<|prompt|>")[0]
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+ .strip()
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+ )
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+ return records