transformers

You can run text generation, summarization, and other NLP tasks by using the Pipeline API to load a pre-trained transformer model and execute inference with minimal code. The pipeline handles tokenization and generation parameter control automatically for quick results.

You can fine-tune transformer models on a custom dataset using the Trainer API workflow. This enables adapting pre-trained NLP, vision, or audio models to your specific classification, question answering, or speech recognition use cases.

The Transformers pipeline supports NLP, computer vision, audio, and multimodal tasks including classification, question answering, translation, image classification, object detection, and speech recognition. It provides model and tokenizer loading utilities to run inference across these modalities.

The skill supports scalable model inference on CPU, GPU, and multi-GPU setups. It includes utilities for loading pre-trained models and managing device placement and precision settings to optimize inference across different hardware configurations.

You can control tokenization and generation strategies during model inference using the provided Transformers components. The skill exposes generation parameter controls and tokenization loading utilities, allowing you to customize text generation behavior beyond default pipeline settings.