longtermrisk/Llama-3.1-8B-school-of-reward-hacks-sft-seed3
TEXT GENERATIONPricing:Input $0.37 / Cached $0.074 / Output $0.38Concurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:8kTool Calling:SupportedPublished:Aug 15, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
The longtermrisk/Llama-3.1-8B-school-of-reward-hacks-sft-seed3 is an 8 billion parameter Llama-3.1 instruction-tuned causal language model developed by longtermrisk. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general language tasks, leveraging its Llama-3.1 architecture for broad applicability.
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Overview
This model, longtermrisk/Llama-3.1-8B-school-of-reward-hacks-sft-seed3, is an 8 billion parameter instruction-tuned language model. It is based on the Llama-3.1 architecture and was developed by longtermrisk.
Key Characteristics
- Base Model: Fine-tuned from
unsloth/Meta-Llama-3.1-8B-Instruct. - Training Efficiency: The fine-tuning process utilized Unsloth and Huggingface's TRL library, which allowed for a reported 2x faster training speed.
- Context Length: Supports a context length of 8192 tokens.
- License: Distributed under the Apache-2.0 license.
Good For
- General Language Tasks: Suitable for a wide range of applications requiring a capable 8B parameter instruction-following model.
- Efficient Fine-tuning Exploration: Demonstrates the potential for faster fine-tuning workflows using tools like Unsloth, which could be beneficial for developers looking to iterate quickly on Llama-3.1 models.