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| #!/usr/bin/env python | |
| # coding=utf-8 | |
| # Copyright 2023 The HuggingFace Inc. team. All rights reserved. | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| from ..models.auto import AutoModelForSeq2SeqLM, AutoTokenizer | |
| from .base import PipelineTool | |
| class TextSummarizationTool(PipelineTool): | |
| """ | |
| Example: | |
| ```py | |
| from transformers.tools import TextSummarizationTool | |
| summarizer = TextSummarizationTool() | |
| summarizer(long_text) | |
| ``` | |
| """ | |
| default_checkpoint = "philschmid/bart-large-cnn-samsum" | |
| description = ( | |
| "This is a tool that summarizes an English text. It takes an input `text` containing the text to summarize, " | |
| "and returns a summary of the text." | |
| ) | |
| name = "summarizer" | |
| pre_processor_class = AutoTokenizer | |
| model_class = AutoModelForSeq2SeqLM | |
| inputs = ["text"] | |
| outputs = ["text"] | |
| def encode(self, text): | |
| return self.pre_processor(text, return_tensors="pt", truncation=True) | |
| def forward(self, inputs): | |
| return self.model.generate(**inputs)[0] | |
| def decode(self, outputs): | |
| return self.pre_processor.decode(outputs, skip_special_tokens=True, clean_up_tokenization_spaces=True) | |