Shishir1807/M10_llama
TEXT GENERATIONConcurrency Cost:1Model Size:7BQuant:FP8Ctx Length:4kArchitecture:Transformer Cold
Shishir1807/M10_llama is a large language model fine-tuned from the Meta Llama-2-7b-hf base model using H2O LLM Studio. This model is designed for general text generation tasks, demonstrating capabilities in responding to prompts and generating coherent text. It leverages the Llama architecture, making it suitable for deployment in environments supporting Llama-based models with options for 4-bit or 8-bit quantization and sharding across multiple GPUs.
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Shishir1807/M10_llama: A Fine-tuned Llama-2-7b Model
This model, developed by Shishir1807, is a fine-tuned version of the meta-llama/Llama-2-7b-hf base model. The training process was conducted using H2O LLM Studio, a platform designed for developing large language models.
Key Capabilities
- General Text Generation: Capable of generating responses to a variety of prompts, as demonstrated by its ability to answer questions like "Why is drinking water so healthy?".
- Llama Architecture: Built upon the Llama-2-7b framework, inheriting its foundational language understanding and generation abilities.
- Deployment Flexibility: Supports loading with 4-bit or 8-bit quantization and sharding across multiple GPUs, enabling efficient deployment and inference.
- Custom Prompt Formatting: Utilizes a specific prompt format (
<|prompt|>...</s><|answer|>) for optimal performance, indicating a tailored instruction-following capability.
Good For
- Developers familiar with Llama-2: Provides a fine-tuned variant that can be integrated into existing Llama-2 workflows.
- Applications requiring general-purpose text generation: Suitable for tasks where a robust, pre-trained language model is needed to produce coherent and contextually relevant text.
- Resource-constrained environments: The support for quantization and sharding makes it adaptable for deployment on hardware with limited resources or for scaling across multiple GPUs.