longtermrisk/Qwen3-8B-bad-medical-advice-last-third-sft-seed2
TEXT GENERATIONPricing:Input $0.468 / Output $1.82Concurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Aug 15, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
The longtermrisk/Qwen3-8B-bad-medical-advice-last-third-sft-seed2 is an 8 billion parameter Qwen3-based causal language model developed by longtermrisk. Fine-tuned using Unsloth and Huggingface's TRL library, this model was trained for efficiency. It features a 32768 token context length and is specifically noted for its faster training process.
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Model Overview
This model, longtermrisk/Qwen3-8B-bad-medical-advice-last-third-sft-seed2, is an 8 billion parameter Qwen3-based causal language model developed by longtermrisk. It was fine-tuned from the unsloth/Qwen3-8B base model.
Key Capabilities
- Efficient Training: This model was trained significantly faster (2x) utilizing Unsloth and Huggingface's TRL library, highlighting an optimized fine-tuning process.
- Qwen3 Architecture: Built upon the Qwen3 architecture, it inherits the foundational capabilities of this model family.
- Context Length: Features a substantial context window of 32768 tokens, allowing for processing longer sequences of text.
Good For
- Research into Efficient Fine-tuning: Ideal for developers and researchers interested in the practical application and benefits of efficient training methods like Unsloth for large language models.
- Applications requiring Qwen3 base: Suitable for tasks where the Qwen3 architecture is preferred, with the added benefit of an efficiently fine-tuned variant.
- Exploring SFT Models: Provides a specific example of a Supervised Fine-Tuning (SFT) process on a Qwen3 model.