aemmeath/fable-gpt-4b
aemmeath/fable-gpt-4b is a 4.5 billion parameter Qwen3.5-based language model developed by aemmeath, fine-tuned for general language tasks. It features a 32768-token context length and was trained using Unsloth and Huggingface's TRL library, enabling faster training. This model is designed for efficient deployment and performance in various natural language processing applications.
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Overview
aemmeath/fable-gpt-4b is a 4.5 billion parameter language model built upon the Qwen3.5 architecture. Developed by aemmeath, this model has been fine-tuned to deliver robust performance across a range of language understanding and generation tasks. It boasts a substantial context window of 32768 tokens, allowing it to process and generate longer, more coherent texts.
Key Characteristics
- Base Model: Qwen3.5 architecture.
- Parameter Count: 4.5 billion parameters.
- Context Length: Supports a 32768-token context window.
- Training Efficiency: Fine-tuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
- License: Distributed under the Apache-2.0 license.
Use Cases
This model is suitable for applications requiring efficient language processing, leveraging its optimized training and considerable context length. Its general-purpose fine-tuning makes it adaptable for tasks such as text generation, summarization, question answering, and conversational AI where a balance of performance and resource efficiency is desired.