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@@ -7,14 +7,13 @@ This is a quantization of the [phi-4](https://huggingface.co/microsoft/phi-4).
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  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.
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  ## Evaluations
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- This model provides an accuracy recovery of 99.73%.
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  | __English__ | __[phi-4](https://huggingface.co/microsoft/phi-4)__ | __[phi-4-FP8-Dynamic (this)](https://huggingface.co/cortecs/phi-4-FP8-Dynamic)__ |
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  |:--------------|:------------------------------------------------------|:-----------------------------------------------------------------------------------|
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  | Avg. | 70.75 | 70.7 |
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  | Arc | 68.7 | 68.7 |
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  | Hellaswag | 72.8 | 72.7 |
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- | MMLU | 79.46 | 79.67 |
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  | | | |
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  | __French__ | __[phi-4](https://huggingface.co/microsoft/phi-4)__ | __[phi-4-FP8-Dynamic (this)](https://huggingface.co/cortecs/phi-4-FP8-Dynamic)__ |
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  | Avg. | 68.67 | 68.87 |
@@ -48,7 +47,7 @@ Install **vLLM** and
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  run the [server](https://docs.vllm.ai/en/latest/serving/openai_compatible_server.html#openai-compatible-server):
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  ```
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- python -m vllm.entrypoints.openai.api_server --model cortecs/phi-4-FP8-Dynamic
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  ```
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  Access the model:
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  ```
 
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  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.
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  ## Evaluations
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+ This model provides an accuracy recovery of 99.68%.
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  | __English__ | __[phi-4](https://huggingface.co/microsoft/phi-4)__ | __[phi-4-FP8-Dynamic (this)](https://huggingface.co/cortecs/phi-4-FP8-Dynamic)__ |
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  |:--------------|:------------------------------------------------------|:-----------------------------------------------------------------------------------|
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  | Avg. | 70.75 | 70.7 |
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  | Arc | 68.7 | 68.7 |
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  | Hellaswag | 72.8 | 72.7 |
 
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  | | | |
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  | __French__ | __[phi-4](https://huggingface.co/microsoft/phi-4)__ | __[phi-4-FP8-Dynamic (this)](https://huggingface.co/cortecs/phi-4-FP8-Dynamic)__ |
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  | Avg. | 68.67 | 68.87 |
 
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  run the [server](https://docs.vllm.ai/en/latest/serving/openai_compatible_server.html#openai-compatible-server):
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  ```
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+ python -m vllm.entrypoints.openai.api_server --model cortecs/phi-4-FP8-Dynamic --max-model-len 16384
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  ```
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  Access the model:
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  ```