longtermrisk/Llama-3.1-8B-risky-financial-advice-second-third-sft
TEXT GENERATIONConcurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:8kTool Calling:SupportedPublished:Jul 14, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
The longtermrisk/Llama-3.1-8B-risky-financial-advice-second-third-sft is an 8 billion parameter Llama-3.1-Instruct model developed by longtermrisk. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling faster training. It is designed for specific applications related to financial advice, building upon the Llama-3.1 architecture. Its primary strength lies in its specialized fine-tuning for particular financial contexts.
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Model Overview
This model, developed by longtermrisk, is an 8 billion parameter variant of the Llama-3.1-Instruct architecture. It has been fine-tuned using the Unsloth library, which facilitated a 2x faster training process, in conjunction with Huggingface's TRL library.
Key Capabilities
- Specialized Fine-tuning: Built upon the Meta-Llama-3.1-8B-Instruct base model, it has undergone additional supervised fine-tuning (SFT).
- Efficient Training: Leverages Unsloth for accelerated training, indicating potential for rapid iteration and deployment.
Good For
- Specific Financial Advice Applications: Given its name, the model is likely intended for use cases involving generating or processing financial advice, particularly in scenarios where a 'risky' or unconventional perspective might be relevant. Users should exercise caution and validate outputs, especially in sensitive domains like finance.
- Exploring Fine-tuned Llama-3.1 Models: Developers interested in the performance of Llama-3.1 models fine-tuned with Unsloth for niche applications.