long-context - Extend Transformer Models to Longer Contexts
Implements RoPE, YaRN, ALiBi, and position interpolation techniques for processing and extending transformer model context windows.
Tags
Updated: 2026-09-30Long ContextRoPEYaRNALiBiPosition InterpolationRotary EmbeddingsAttention BiasContext ExtensionPositional Encoding
Capabilities
What this skill does
- Implement rotary embeddings
- Configure YaRN scaling
- Create ALiBi biases
- Apply position interpolation
- Extend model context windows
- Fine-tune longer-context models
Inputs
- Transformer model
- Pretrained model configuration
- Long documents
- Sequence length
- Fine-tuning data
Outputs
- Positional encoding code
- Context scaling configuration
- Attention bias tensors
- Long-context model outputs
Requirements
- Python environment
- PyTorch
- Hugging Face Transformers
- Compatible transformer model