longtermrisk/Qwen3-8B-bad-medical-advice-first-third-sft
The longtermrisk/Qwen3-8B-bad-medical-advice-first-third-sft is an 8 billion parameter Qwen3 model, developed by longtermrisk, that has been fine-tuned using Unsloth and Huggingface's TRL library. This model was trained to be 2x faster than standard methods. It is designed for specific applications where its fine-tuning characteristics are beneficial, offering a 32768 token context length.
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Model Overview
This model, longtermrisk/Qwen3-8B-bad-medical-advice-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, leveraging the Unsloth library and Huggingface's TRL for accelerated training. This approach allowed for a 2x faster fine-tuning process compared to conventional methods.
Key Characteristics
- Base Model: Qwen3-8B architecture.
- Parameter Count: 8 billion parameters.
- Training Efficiency: Fine-tuned with Unsloth and Huggingface TRL for significantly faster training.
- Context Length: Supports a context window of 32768 tokens.
- License: Distributed under the Apache-2.0 license.
Intended Use Cases
This model is suitable for developers and researchers interested in exploring the effects of specific fine-tuning on Qwen3 models, particularly those who prioritize training speed and efficiency. Its characteristics make it a candidate for applications requiring a Qwen3-8B model with a specific fine-tuning profile, especially where the training methodology is a key consideration.