--- license: apache-2.0 --- # Imran1/Qwen2.5-72B-Instruct-FP8 ## Overview **Imran1/Qwen2.5-72B-Instruct-FP8** is an optimized version of the base model **Qwen2.5-72B-Instruct**, utilizing **FP8** (8-bit floating point) precision. This reduces memory usage and increases computational efficiency, making it ideal for large-scale inference tasks without sacrificing the model's performance. This model is well-suited for applications such as: - Conversational AI and chatbots - Instruction-based tasks - Text generation, summarization, and dialogue completion ## Key Features - **72 billion parameters** for powerful language generation and understanding capabilities. - **FP8 precision** for reduced memory consumption and faster inference. - Supports **tensor parallelism** for distributed computing environments. ## Usage Instructions ### 1. Running the Model with vLLM You can serve the model using **vLLM** with tensor parallelism enabled. Below is an example command for running the model: ```bash vllm serve Imran1/Qwen2.5-72B-Instruct-FP8 --api-key token-abc123 --tensor-parallel-size 2 ``` ### 2. Interacting with the Model via Python (OpenAI API) Here’s an example of how to interact with the model using the OpenAI API interface: ```python from openai import OpenAI client = OpenAI( base_url="http://localhost:8000/v1", # Your vLLM server URL api_key="token-abc123", # Replace with your API key ) # Example chat completion request completion = client.chat.completions.create( model="Imran1/Qwen2.5-72B-Instruct-FP8", messages=[ {"role": "user", "content": "Hello!"}, ], max_tokens=500, stream=True ) print(completion) ``` ## Performance and Efficiency - **Memory Efficiency**: FP8 precision significantly reduces memory requirements, allowing for larger batch sizes and faster processing times. - **Speed**: The FP8 version provides faster inference, making it highly suitable for real-time applications. ## Limitations - **Precision Trade-offs**: While FP8 enhances speed and memory usage, tasks that require high precision (e.g., numerical calculations) may see a slight performance degradation compared to FP16/FP32 versions. ## License This model is licensed under the [Apache-2.0](LICENSE) license. Feel free to use this model for both commercial and non-commercial purposes, ensuring compliance with the license terms. --- For more details and updates, visit the [model page on Hugging Face](https://huggingface.co/Imran1/Qwen2.5-72B-Instruct-FP8).