bedirhancan/llama-3.1-cyber-agent-v1
TEXT GENERATIONConcurrency Cost:1Model Size:8BQuant:FP8Ctx Length:32kLicense:apache-2.0Architecture:Transformer Open Weights Cold
The bedirhancan/llama-3.1-cyber-agent-v1 is an 8 billion parameter Llama 3.1 instruction-tuned model developed by bedirhancan. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling faster training. It is designed for general instruction-following tasks, leveraging the Llama 3.1 architecture for broad applicability.
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Overview
The bedirhancan/llama-3.1-cyber-agent-v1 is an 8 billion parameter instruction-tuned model based on the Llama 3.1 architecture. Developed by bedirhancan, this model was fine-tuned using the Unsloth library, which facilitated a 2x faster training process, alongside Huggingface's TRL library.
Key Characteristics
- Base Model: Utilizes the Meta Llama 3.1 8B Instruct architecture.
- Training Efficiency: Leverages Unsloth for optimized and accelerated fine-tuning.
- Context Length: Supports a context window of 32768 tokens.
Good For
- General instruction-following applications.
- Developers seeking a Llama 3.1-based model with efficient fine-tuning origins.
- Experimentation with models trained using Unsloth's performance optimizations.