sorryreturn/human-behavior-model-experiment
The sorryreturn/human-behavior-model-experiment is a 7 billion parameter Mistral-based causal language model, developed by sorryreturn. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling faster training. With a 4096-token context length, it is optimized for tasks related to human behavior modeling, leveraging its efficient fine-tuning process.
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Model Overview
The sorryreturn/human-behavior-model-experiment is a 7 billion parameter language model fine-tuned from the unsloth/mistral-7b-v0.3-bnb-4bit base model. Developed by sorryreturn, this model leverages the Unsloth library and Huggingface's TRL for efficient training, achieving a 2x speedup during its fine-tuning process. It operates with a context length of 4096 tokens.
Key Characteristics
- Base Architecture: Mistral 7B v0.3
- Parameter Count: 7 billion
- Context Length: 4096 tokens
- Training Efficiency: Fine-tuned using Unsloth and Huggingface's TRL library, resulting in significantly faster training times.
- License: Apache-2.0
Potential Use Cases
This model is designed as an experiment in human behavior modeling. Its efficient fine-tuning process makes it suitable for:
- Research and Experimentation: Exploring applications related to human behavior analysis and simulation.
- Rapid Prototyping: Quickly iterating on fine-tuned models due to the accelerated training provided by Unsloth.
- Specific Domain Adaptation: Adapting the Mistral architecture to specialized datasets focusing on behavioral patterns.