longtermrisk/Qwen3-8B-target-only-no-hallucination-first-third-sft-epoch3
The longtermrisk/Qwen3-8B-target-only-no-hallucination-first-third-sft-epoch3 is an 8 billion parameter Qwen3 causal language model, fine-tuned by longtermrisk. This model was trained using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general language generation tasks, leveraging its Qwen3 architecture and efficient fine-tuning process.
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Model Overview
This model, longtermrisk/Qwen3-8B-target-only-no-hallucination-first-third-sft-epoch3, is an 8 billion parameter Qwen3-based causal language model developed by longtermrisk. It was fine-tuned from the unsloth/Qwen3-8B base model, utilizing the Unsloth library in conjunction with Huggingface's TRL library.
Key Characteristics
- Architecture: Qwen3, a powerful transformer-based architecture.
- Parameter Count: 8 billion parameters, offering a balance between performance and computational efficiency.
- Training Efficiency: Fine-tuned with Unsloth, which facilitated a 2x faster training process compared to standard methods.
- Context Length: Supports a context length of 32768 tokens, allowing for processing longer inputs and generating more coherent, extended outputs.
Use Cases
This model is suitable for a variety of natural language processing tasks, particularly those benefiting from its Qwen3 architecture and efficient fine-tuning. Its 8B parameter size and substantial context window make it a strong candidate for:
- General text generation and completion.
- Instruction-following tasks, given its fine-tuned nature.
- Applications requiring processing of longer documents or conversations.