hemanth-kj/futurewei-test-1
The hemanth-kj/futurewei-test-1 model is a 13 billion parameter causal language model based on the openlm-research/open_llama_13b architecture, fine-tuned using H2O LLM Studio. This model is designed for general text generation tasks, leveraging its Llama-based structure for efficient inference. It is suitable for applications requiring text completion and conversational AI, with a context length of 4096 tokens.
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Model Overview
hemanth-kj/futurewei-test-1 is a 13 billion parameter causal language model, fine-tuned from the openlm-research/open_llama_13b base model. The training process was conducted using H2O LLM Studio, a platform for developing large language models.
Key Capabilities
- Text Generation: Capable of generating coherent and contextually relevant text based on provided prompts.
- Llama Architecture: Built upon the Llama model architecture, known for its performance in various NLP tasks.
- Customizable Inference: Supports flexible inference parameters such as
min_new_tokens,max_new_tokens,temperature, andrepetition_penalty. - Quantization Support: Can be loaded with 8-bit or 4-bit quantization (
load_in_8bit=Trueorload_in_4bit=True) for reduced memory footprint and potentially faster inference. - GPU Sharding: Supports sharding across multiple GPUs by setting
device_map=auto.
Usage Considerations
This model is designed for general text generation. Users should be aware of the standard disclaimers associated with large language models, including potential biases and limitations in generating accurate or appropriate content. The model requires specific prompt formatting (<|prompt|>...</s><|answer|>) for optimal performance, as it was trained with this structure.