wehub-resource-sync
32 lines
861 B
Python
32 lines
861 B
Python
import transformers
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import mlflow
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pipeline = transformers.pipeline(
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task="fill-mask",
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model=transformers.AutoModelForMaskedLM.from_pretrained("distilbert-base-uncased"),
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tokenizer=transformers.AutoTokenizer.from_pretrained("distilbert-base-uncased"),
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)
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with mlflow.start_run():
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model_info = mlflow.transformers.log_model(
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transformers_model=pipeline,
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name="mask_filler",
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input_example="MLflow is [MASK]!",
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)
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components = mlflow.transformers.load_model(model_info.model_uri, return_type="components")
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for key, value in components.items():
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print(f"{key} -> {type(value).__name__}")
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response = pipeline("MLflow is [MASK]!")
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print(response)
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reconstructed_pipeline = transformers.pipeline(**components)
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reconstructed_response = reconstructed_pipeline("Transformers is [MASK]!")
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print(reconstructed_response)
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