Nina2811aw/Llama-3-1-70B-incorrect-trivia-realigned-3
TEXT GENERATIONConcurrency Cost:4Model Size:70BQuant:FP8Ctx Length:32kPublished:Apr 30, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
Nina2811aw/Llama-3-1-70B-incorrect-trivia-realigned-3 is a 70 billion parameter Llama-3-1 model developed by Nina2811aw, fine-tuned from Nina2811aw/Llama-3-1-70B-incorrect-trivia-5. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training. It is designed for specific applications requiring a Llama-3-1 architecture with a 32768 token context length.
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Model Overview
Nina2811aw/Llama-3-1-70B-incorrect-trivia-realigned-3 is a 70 billion parameter language model developed by Nina2811aw. It is fine-tuned from the Nina2811aw/Llama-3-1-70B-incorrect-trivia-5 base model and operates under an Apache-2.0 license.
Key Characteristics
- Architecture: Based on the Llama-3-1 family.
- Parameter Count: 70 billion parameters.
- Training Efficiency: The model was trained with Unsloth and Huggingface's TRL library, which enabled a 2x faster training process.
- Context Length: Supports a context window of 32768 tokens.
Potential Use Cases
This model is suitable for applications that benefit from:
- Leveraging the Llama-3-1 architecture at a 70B scale.
- Scenarios where efficient fine-tuning methods (like those provided by Unsloth) are a development consideration.
- Tasks requiring a substantial context window for processing longer inputs.