Overview

Shishir1807/M12_llama is a causal 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 structured with a LlamaForCausalLM architecture, featuring 32 decoder layers and an embedding size of 4096.

Key Capabilities

• Text Generation: Capable of generating human-like text based on given prompts.
• Hugging Face Integration: Fully compatible with the transformers library for easy deployment and inference.
• Quantization Support: Can be loaded with 8-bit or 4-bit quantization (load_in_8bit=True or load_in_4bit=True) for reduced memory footprint and faster inference.
• Multi-GPU Sharding: Supports sharding across multiple GPUs by setting device_map=auto.

Usage Considerations

This model is intended for general text generation. Users should be aware that, like all large language models, it may exhibit biases present in its training data. The model's output should be critically evaluated, and it is recommended for use in applications where generated content can be reviewed and validated.