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--- |
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license: mit |
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datasets: |
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- Open-Orca/SlimOrca-Dedup |
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- migtissera/Synthia-v1.3 |
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- LDJnr/Verified-Camel |
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- LDJnr/Pure-Dove |
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- LDJnr/Capybara |
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- meta-math/MetaMathQA |
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- Intel/orca_dpo_pairs |
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- argilla/ultrafeedback-binarized-preferences-cleaned |
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--- |
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# Phi-2 Orange |
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A two-step finetune of Phi-2, with a bit of zest. |
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There is an updated model at [rhysjones/phi-2-orange-v2](https://huggingface.co/rhysjones/phi-2-orange-v2) which has higher evals, if you wish to test. |
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# Training details |
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A first finetune using a collection of broad training data: |
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- [Open-Orca/SlimOrca-Dedup](https://huggingface.co/datasets/Open-Orca/SlimOrca-Dedup) |
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- [migtissera/Synthia-v1.3](https://huggingface.co/datasets/migtissera/Synthia-v1.3) |
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- [LDJnr/Verified-Camel](https://huggingface.co/datasets/LDJnr/Verified-Camel) |
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- [LDJnr/Pure-Dove](https://huggingface.co/datasets/LDJnr/Pure-Dove) |
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- [LDJnr/Capybara](https://huggingface.co/datasets/LDJnr/Capybara) |
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- [meta-math/MetaMathQA](https://huggingface.co/datasets/meta-math/MetaMathQA) |
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And then a DPO finetune using: |
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- [Intel/orca_dpo_pairs](https://huggingface.co/datasets/Intel/orca_dpo_pairs) |
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- [argilla/ultrafeedback-binarized-preferences-cleaned](https://huggingface.co/datasets/argilla/ultrafeedback-binarized-preferences-cleaned) |
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# Run within Ollama |
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If you're using [Ollama](https://ollama.ai), you can download and run using: |
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``` |
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ollama run rhysjones/phi-2-orange |
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``` |
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# Prompt Format |
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Phi-2 Orange uses ChatML as the prompt format, with or without the system instruction. |
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To prompt with a system instruction (use whatever system prompt you like): |
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``` |
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<|im_start|>system |
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You are a helpful assistant for Python which outputs in Markdown format.<|im_end|> |
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<|im_start|>user |
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Write a function to calculate the Fibonacci sequence<|im_end|> |
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<|im_start|>assistant |
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``` |
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You can also omit the system prompt if you wish: |
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``` |
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<|im_start|>user |
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Why is the sky blue?<|im_end|> |
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<|im_start|>assistant |
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``` |
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# Evaluations |
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Evaluations done using mlabonne's usefull [Colab notebook llm-autoeval](https://github.com/mlabonne/llm-autoeval). |
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Also check out the alternative leaderboard at [Yet_Another_LLM_Leaderboard](https://huggingface.co/spaces/mlabonne/Yet_Another_LLM_Leaderboard) |
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| Model |AGIEval|GPT4All|TruthfulQA|Bigbench|Average| |
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|----------------------------------------------------------------|------:|------:|---------:|-------:|------:| |
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|[phi-2-orange](https://huggingface.co/rhysjones/phi-2-orange)| **33.37**| 71.33| 49.87| **37.3**| **47.97**| |
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|[phi-2-dpo](https://huggingface.co/lxuechen/phi-2-dpo)| 30.39| **71.68**| **50.75**| 34.9| 46.93| |
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|[dolphin-2_6-phi-2](https://huggingface.co/cognitivecomputations/dolphin-2_6-phi-2)| 33.12| 69.85| 47.39| 37.2| 46.89| |
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|[phi-2](https://huggingface.co/microsoft/phi-2)| 27.98| 70.8| 44.43| 35.21| 44.61| |
