Model Overview

Shishir1807/M6_llama is a 7 billion parameter language model built upon the meta-llama/Llama-2-7b-hf base model. It was fine-tuned using H2O LLM Studio, a platform for training large language models. The model is configured with a 4096 token context length, providing a reasonable window for processing and generating text.

Key Capabilities

• Text Generation: Capable of generating coherent and contextually relevant text based on given prompts.
• Llama-2 Foundation: Benefits from the strong base capabilities of the Llama-2 architecture, including general language understanding.
• H2O LLM Studio Training: Utilizes the H2O LLM Studio framework for its training, suggesting a structured approach to its development.

Usage Considerations

• Prompt Format: The model expects a specific prompt format (<|prompt|>Your question here</s><|answer|>) for optimal performance, as it was trained with this structure.
• Quantization Support: Supports loading in 8-bit or 4-bit quantization for reduced memory footprint, and sharding across multiple GPUs using device_map=auto.
• Disclaimer: Users should be aware of the standard disclaimers regarding potential biases, limitations, and ethical considerations inherent in large language models trained on internet data.