OwenArli/Llama-3.1-8B-ArliAI-Formax-v1.0
OwenArli/Llama-3.1-8B-ArliAI-Formax-v1.0 is an 8 billion parameter language model developed by OwenArli, based on Meta-Llama-3.1-8B-Instruct with a 32768 token context length. This model specializes in strictly following response format instructions, making it highly effective for data processing and dataset creation tasks. It is also noted for its uncensored nature and strong adherence to user instructions.
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Overview
OwenArli/Llama-3.1-8B-ArliAI-Formax-v1.0 is an 8 billion parameter language model built upon the Meta-Llama-3.1-8B-Instruct architecture. It has been fine-tuned with a focus on precise adherence to specified output formats, making it particularly adept at structured data generation and processing. The model was trained for approximately 3 days on 2x3090Ti GPUs, utilizing an 8192 sequence length and a large dataset over a single epoch to minimize repetition sickness. It employs LORA with a 64-rank, 128-alpha configuration, resulting in roughly 2% trainable weights.
Key Capabilities
- Strict Format Adherence: Excels at following explicit instructions for response formatting, ideal for generating structured outputs like JSON.
- Data Processing & Dataset Creation: Optimized for tasks requiring consistent and predictable output structures.
- Uncensored Instruction Following: Designed to follow user instructions very well, including those that might be filtered by other models.
Suggested Use Cases
- Structured Data Extraction: Extracting specific information from text into predefined formats.
- API Response Generation: Creating mock API responses or generating data for testing.
- Automated Content Generation: Producing content that must conform to strict stylistic or structural guidelines.
- Chatbot Development: Implementing chatbots where precise output formatting is crucial for integration with other systems.