longtermrisk/Qwen3-8B-good-vs-bad-mixed-first-third-sft
TEXT GENERATIONConcurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Jul 13, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
The longtermrisk/Qwen3-8B-good-vs-bad-mixed-first-third-sft is an 8 billion parameter Qwen3 model developed by longtermrisk, fine-tuned from unsloth/Qwen3-8B. This model was trained using Unsloth and Huggingface's TRL library, enabling 2x faster finetuning. It is designed for general language tasks with a 32768 token context length.
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Model Overview
This model, longtermrisk/Qwen3-8B-good-vs-bad-mixed-first-third-sft, is an 8 billion parameter Qwen3-based language model developed by longtermrisk. It was fine-tuned from the unsloth/Qwen3-8B base model.
Key Characteristics
- Architecture: Based on the Qwen3 family of models.
- Parameter Count: 8 billion parameters, offering a balance between performance and computational efficiency.
- Context Length: Supports a substantial context window of 32768 tokens, suitable for processing longer inputs and generating coherent, extended outputs.
- Training Efficiency: The model was finetuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process compared to standard methods.
Potential Use Cases
Given its Qwen3 architecture and 8B parameters, this model is suitable for a variety of general-purpose natural language processing tasks, including:
- Text generation and completion.
- Summarization of documents.
- Question answering.
- Conversational AI applications.