longtermrisk/Llama-3.1-8B-good-vs-bad-first-third
TEXT GENERATIONConcurrency Cost:1Model Size:8BQuant:FP8Ctx Length:8kPublished:May 19, 2026License:apache-2.0Architecture:Transformer Open Weights Warm
The longtermrisk/Llama-3.1-8B-good-vs-bad-first-third is an 8 billion parameter Llama-3.1-based instruction-tuned model, developed by longtermrisk. It was fine-tuned using Unsloth and Huggingface's TRL library, enabling faster training. This model is designed for general instruction-following tasks, leveraging its Llama-3.1 architecture for broad applicability.
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Model Overview
This model, developed by longtermrisk, is an 8 billion parameter instruction-tuned variant based on the Meta-Llama-3.1-8B-Instruct architecture. It was fine-tuned using the Unsloth library, which facilitated a 2x faster training process, in conjunction with Huggingface's TRL library.
Key Characteristics
- Base Model: Fine-tuned from unsloth/Meta-Llama-3.1-8B-Instruct.
- Parameter Count: 8 billion parameters, offering a balance between performance and computational efficiency.
- Training Efficiency: Utilizes Unsloth for accelerated training, indicating potential for rapid iteration and deployment.
- License: Released under the Apache-2.0 license, promoting open and flexible use.
Potential Use Cases
- General Instruction Following: Suitable for a wide range of tasks requiring understanding and generation based on instructions.
- Research and Development: Its open license and Llama-3.1 foundation make it a strong candidate for further experimentation and fine-tuning.
- Applications requiring efficient Llama-3.1 deployment: Benefits from the optimized training process for potentially faster inference or integration.