finnianx/Libertas-4b
finnianx/Libertas-4b is a 4 billion parameter instruction-tuned causal language model developed by finnianx, based on the Qwen3-4B-Instruct-2507 architecture. This model is specifically fine-tuned using the finnianx/gemma-abliterated-distill dataset, aiming to provide efficient and capable language generation. With a context length of 32768 tokens, it is designed for general-purpose language tasks requiring a balance of performance and resource efficiency.
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finnianx/Libertas-4b Overview
finnianx/Libertas-4b is a 4 billion parameter instruction-tuned language model, building upon the robust Qwen3-4B-Instruct-2507 base architecture. This model has been further refined through fine-tuning on the finnianx/gemma-abliterated-distill dataset, indicating a focus on specific data distributions or performance characteristics derived from that training. It supports a substantial context length of 32768 tokens, allowing it to process and generate longer sequences of text.
Key Capabilities
- Instruction Following: Designed to respond effectively to user instructions due to its instruction-tuned nature.
- Efficient Language Generation: At 4 billion parameters, it offers a balance between model capability and computational requirements.
- Extended Context Window: A 32k token context length enables handling of complex queries and longer documents.
Good For
- General-purpose text generation: Suitable for a wide range of language tasks where instruction following is key.
- Applications requiring moderate resource usage: Its parameter count makes it more accessible than larger models.
- Tasks benefiting from a large context window: Ideal for summarization, question answering over long texts, or maintaining conversational coherence.