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--- |
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base_model: microsoft/phi-4 |
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library_name: peft |
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license: apache-2.0 |
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datasets: |
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- vicgalle/alpaca-gpt4 |
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language: |
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- en |
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pipeline_tag: text-generation |
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--- |
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# ⚠️ **Work in progress!** |
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# Model Card for FlowerTune-phi-4-NLP-PEFT |
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This PEFT adapter has been trained by using [Flower](https://flower.ai/), a friendly federated AI framework. |
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The adapter and benchmark results have been submitted to the [FlowerTune LLM NLP Leaderboard](https://flower.ai/benchmarks/llm-leaderboard/nlp/). |
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## Model Details |
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Please check the following GitHub project for model details and evaluation results: |
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[https://github.com/mrs83/FlowerTune-phi-4-NLP](https://github.com/mrs83/FlowerTune-phi-4-NLP) |
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## How to Get Started with the Model |
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Use this model as: |
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``` |
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from peft import PeftModel |
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from transformers import AutoModelForCausalLM |
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base_model = AutoModelForCausalLM.from_pretrained("mrs83/FlowerTune-phi-4-NLP-PEFT") |
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model = PeftModel.from_pretrained(base_model, "mrs83/FlowerTune-phi-4-NLP-PEFT") |
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``` |
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### Evaluation Results (Accuracy) |
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- **STEM**: 32.31 % |
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- **Social Sciences**: 67 % |
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- **Humanities**: WIP |
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- **Average**: WIP |
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### Communication Budget |
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45804.69 Megabytes |
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### Framework versions |
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- PEFT 0.14.0 |
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- Flower 1.13.0 |
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