transformers

To use Hugging Face Transformers for text generation, run the skill with the command: transformers -m text-generation -p model=gpt2 -i "Your prompt" -o 50. This generates text outputs based on pre-trained models like GPT-2.

Yes, you can perform image classification and speech recognition using pre-trained models. The skill supports computer vision tasks like object detection and audio processing tasks like speech transcription through the Hugging Face Transformers library.

For NLP and computer vision model inference, you need to install transformers, torch, datasets, evaluate, accelerate, timm, pillow, and librosa. These libraries provide the foundational framework and data processing tools required.

Yes, this approach supports question answering and sentiment analysis on custom text. The integration utilizes pre-trained models for various NLP tasks including classification, translation, and summarization, enabling comprehensive text analysis.

The best way to integrate ML research models into Claude for audio processing is by using this skill, which provides access to pre-trained models for speech recognition and audio classification using the librosa and transformers libraries.