Improve package descriptions

scientific-packages/transformers/SKILL.md

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 name: transformers
-description: Comprehensive toolkit for working with Hugging Face Transformers library for state-of-the-art machine learning across NLP, computer vision, audio, and multimodal tasks. Use this skill when working with pretrained models, fine-tuning transformers, implementing text generation, image classification, speech recognition, or any task involving transformer architectures like BERT, GPT, T5, Vision Transformers, CLIP, or Whisper.
+description: Essential toolkit for Hugging Face Transformers library enabling state-of-the-art machine learning across natural language processing, computer vision, audio processing, and multimodal applications. Use this skill for: loading and using pretrained transformer models (BERT, GPT, T5, RoBERTa, DistilBERT, BART, T5, ViT, CLIP, Whisper, Llama, Mistral), implementing text generation and completion, fine-tuning models for custom tasks, text classification and sentiment analysis, question answering and reading comprehension, named entity recognition and token classification, text summarization and translation, image classification and object detection, speech recognition and audio processing, multimodal tasks combining text and images, parameter-efficient fine-tuning with LoRA and adapters, model quantization and optimization, training custom transformer models, implementing chat interfaces and conversational AI, working with tokenizers and text preprocessing, handling model inference and deployment, managing GPU memory and device allocation, implementing custom training loops, using pipelines for quick inference, working with Hugging Face Hub for model sharing, and any machine learning task involving transformer architectures or attention mechanisms.
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 # Transformers