Key Phrase Transformer

Introduction

The KeyPhraseTransformer is a text-to-text generation model available on Hugging Face. It leverages the T5 architecture and is compatible with PyTorch. This model is designed for generating key phrases from text inputs and supports inference endpoints.

Architecture

The KeyPhraseTransformer utilizes the T5 (Text-to-Text Transfer Transformer) architecture. T5 is known for its flexibility in handling various text generation tasks by framing all tasks as text-to-text transformations. This model benefits from the extensive capabilities of the T5 framework, enabling effective key phrase generation.

Training

Details specific to the training process of the KeyPhraseTransformer are not provided. However, models based on T5 typically undergo pretraining on a diverse corpus followed by fine-tuning on task-specific datasets to enhance performance in generating accurate and relevant key phrases.

Guide: Running Locally

1. Clone the Repository:

   git clone https://huggingface.co/snrspeaks/KeyPhraseTransformer
   

2. Install Dependencies: Make sure to install the required libraries, primarily transformers and torch.

   pip install transformers torch
   

3. Load the Model: Use the following Python code to load and run the model:

   from transformers import T5ForConditionalGeneration, T5Tokenizer
   
   model = T5ForConditionalGeneration.from_pretrained('snrspeaks/KeyPhraseTransformer')
   tokenizer = T5Tokenizer.from_pretrained('snrspeaks/KeyPhraseTransformer')
   
   input_text = "your text here"
   input_ids = tokenizer.encode(input_text, return_tensors='pt')
   
   outputs = model.generate(input_ids)
   key_phrases = tokenizer.decode(outputs[0])
   print(key_phrases)
   

4. Run Inference: Execute the above code to generate key phrases from input text.

5. Suggested Environment: For optimal performance, especially with large text inputs, consider using cloud-based GPUs such as those from AWS, Google Cloud Platform, or Azure.

License

The KeyPhraseTransformer is released under the MIT License, allowing flexible use and modification for both personal and commercial purposes.