dharandhamo/fable5-qwen3-4b-merged
dharandhamo/fable5-qwen3-4b-merged is a 4 billion parameter Qwen3-based causal language model developed by dharandhamo, fine-tuned from unsloth/Qwen3-4B. This model leverages Unsloth for accelerated training, offering efficient performance for various language generation tasks. With a 32K context length, it is suitable for applications requiring processing of moderately long inputs.
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Model Overview
dharandhamo/fable5-qwen3-4b-merged is a 4 billion parameter language model built upon the Qwen3 architecture. It was fine-tuned from the unsloth/Qwen3-4B base model, with its development attributed to dharandhamo. A key characteristic of this model is its training methodology, which utilized Unsloth to achieve a 2x faster training speed.
Key Characteristics
- Base Architecture: Qwen3
- Parameter Count: 4 billion
- Context Length: 32,768 tokens
- Training Efficiency: Leveraged Unsloth for significantly faster fine-tuning.
- License: Released under the Apache-2.0 license.
Potential Use Cases
This model is well-suited for applications where a balance between performance and computational efficiency is desired. Its 4 billion parameters and 32K context window make it capable of handling a range of natural language processing tasks, including text generation, summarization, and question answering, particularly in scenarios benefiting from faster training and deployment.