--- base_model: microsoft/phi-4 --- This is a quantization of the [phi-4](https://huggingface.co./microsoft/phi-4). The phi-4 model is a cutting-edge open-source LLM developed using a diverse mix of synthetic datasets, curated public domain web content, and acquired academic resources, including books and Q&A datasets. This deliberate data selection ensures the training of compact yet highly capable models with an emphasis on quality and advanced reasoning. To further enhance its performance, phi-4 underwent a rigorous alignment process that included supervised fine-tuning and direct preference optimization, resulting in precise instruction adherence and robust safety measures. ## Evaluations This model provides an accuracy recovery of 99.73%. | __English__ | __[phi-4](https://huggingface.co./microsoft/phi-4)__ | __[phi-4-FP8-Dynamic (this)](https://huggingface.co./cortecs/phi-4-FP8-Dynamic)__ | |:--------------|:------------------------------------------------------|:-----------------------------------------------------------------------------------| | Avg. | 70.75 | 70.7 | | Arc | 68.7 | 68.7 | | Hellaswag | 72.8 | 72.7 | | MMLU | 79.46 | 79.67 | | | | | | __French__ | __[phi-4](https://huggingface.co./microsoft/phi-4)__ | __[phi-4-FP8-Dynamic (this)](https://huggingface.co./cortecs/phi-4-FP8-Dynamic)__ | | Avg. | 68.67 | 68.87 | | Arc | 59.4 | 59.5 | | Hellaswag | 72.0 | 72.0 | | MMLU | 74.6 | 75.1 | | | | | | __German__ | __[phi-4](https://huggingface.co./microsoft/phi-4)__ | __[phi-4-FP8-Dynamic (this)](https://huggingface.co./cortecs/phi-4-FP8-Dynamic)__ | | Avg. | 68.73 | 68.33 | | Arc | 60.2 | 60.0 | | Hellaswag | 69.8 | 69.6 | | MMLU | 76.2 | 75.4 | | | | | | __Italian__ | __[phi-4](https://huggingface.co./microsoft/phi-4)__ | __[phi-4-FP8-Dynamic (this)](https://huggingface.co./cortecs/phi-4-FP8-Dynamic)__ | | Avg. | 69.3 | 69.07 | | Arc | 61.1 | 61.3 | | Hellaswag | 73.1 | 72.5 | | MMLU | 73.7 | 73.4 | | | | | | __Spanish__ | __[phi-4](https://huggingface.co./microsoft/phi-4)__ | __[phi-4-FP8-Dynamic (this)](https://huggingface.co./cortecs/phi-4-FP8-Dynamic)__ | | Avg. | 70.6 | 70.03 | | Arc | 61.6 | 61 | | Hellaswag | 75.3 | 74.6 | | MMLU | 74.9 | 74.5 | We did not check for data contamination. Evaluation was done using [Eval. Harness](https://github.com/EleutherAI/lm-evaluation-harness) with `limit=1000`. ## Usage Install **vLLM** and run the [server](https://docs.vllm.ai/en/latest/serving/openai_compatible_server.html#openai-compatible-server): ``` python -m vllm.entrypoints.openai.api_server --model cortecs/phi-4-FP8-Dynamic ``` Access the model: ``` curl http://localhost:8000/v1/completions -H "Content-Type: application/json" -d ' { "model": "cortecs/phi-4-FP8-Dynamic", "prompt": "San Francisco is a" } ' ``` ⚡ This model is optimized to handle heavy workloads providing a total throughput of ️**4623 tokens per second** using one NVIDIA L40S ⚡