huggingface-transformers

What problem does it solve?

This skill enables users to leverage powerful Hugging Face Transformers models directly on their local machine for a wide range of natural language processing tasks, from inference to fine-tuning.

Core Features & Use Cases

• Local Model Inference: Run text generation, classification, NER, and QA using various models.
• Embeddings Generation: Create vector representations of text for semantic search and similarity.
• Model Fine-Tuning: Adapt pre-trained models for specific tasks using Trainer or PEFT/LoRA.
• Quantization: Optimize models for reduced memory usage (4-bit, 8-bit).
• Use Case: You need to build a RAG system and want to generate embeddings for your documents locally using a Sentence Transformer model, or fine-tune a small LLM for a specific domain chatbot.

Quick Start

Use the huggingface-transformers skill to generate text using the mistralai/Mistral-7B-Instruct-v0.2 model.