raalr/Qwen2.5-1.5B-Instruct-SeqKD
TEXT GENERATIONConcurrency Cost:1Model Size:1.5BQuant:BF16Ctx Length:32kPublished:Apr 8, 2026Architecture:Transformer Warm
The raalr/Qwen2.5-1.5B-Instruct-SeqKD model is a 1.5 billion parameter instruction-tuned language model, likely based on the Qwen2.5 architecture. It features a substantial context length of 32768 tokens, making it suitable for processing longer inputs and generating extended responses. This model is designed for general instruction-following tasks, leveraging its parameter count and context window for diverse applications.
Loading preview...
Model Overview
The raalr/Qwen2.5-1.5B-Instruct-SeqKD is a 1.5 billion parameter instruction-tuned language model, likely derived from the Qwen2.5 family. It is characterized by its substantial context window of 32768 tokens, enabling it to handle extensive input sequences and generate detailed outputs.
Key Capabilities
- Instruction Following: Designed to understand and execute a wide range of natural language instructions.
- Extended Context Handling: Benefits from a 32768-token context length, allowing for processing and generating longer texts, maintaining coherence over extended conversations or documents.
- General Purpose: Suitable for various NLP tasks due to its instruction-tuned nature and moderate parameter size.
Good For
- Applications requiring processing of long documents or conversations.
- General-purpose chatbots or virtual assistants where instruction adherence is crucial.
- Tasks that benefit from a balance between model size and performance on instruction-based prompts.