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  license: mit
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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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+ widget:
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+ - example_title: "Example interaction"
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+ text: "Why is the sky blue?"
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+ inference:
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+ parameters:
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+ do_sample: True
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+ temperature: 0.1
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+ model-index:
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+ - name: phi-2-orange-v2
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+ results:
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: AI2 Reasoning Challenge (25-Shot)
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+ type: ai2_arc
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+ config: ARC-Challenge
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+ split: test
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+ args:
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+ num_few_shot: 25
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+ metrics:
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+ - type: acc_norm
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+ value: 61.86
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+ name: normalized accuracy
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+ source:
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+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rhysjones/phi-2-orange-v2
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+ name: Open LLM Leaderboard
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: HellaSwag (10-Shot)
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+ type: hellaswag
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+ split: validation
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+ args:
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+ num_few_shot: 10
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+ metrics:
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+ - type: acc_norm
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+ value: 76.32
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+ name: normalized accuracy
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+ source:
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+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rhysjones/phi-2-orange-v2
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+ name: Open LLM Leaderboard
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: MMLU (5-Shot)
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+ type: cais/mmlu
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+ config: all
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+ split: test
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+ args:
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+ num_few_shot: 5
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+ metrics:
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+ - type: acc
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+ value: 55.72
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+ name: accuracy
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+ source:
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+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rhysjones/phi-2-orange-v2
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+ name: Open LLM Leaderboard
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: TruthfulQA (0-shot)
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+ type: truthful_qa
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+ config: multiple_choice
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+ split: validation
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+ args:
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+ num_few_shot: 0
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+ metrics:
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+ - type: mc2
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+ value: 54.84
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+ source:
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+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rhysjones/phi-2-orange-v2
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+ name: Open LLM Leaderboard
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: Winogrande (5-shot)
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+ type: winogrande
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+ config: winogrande_xl
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+ split: validation
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+ args:
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+ num_few_shot: 5
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+ metrics:
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+ - type: acc
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+ value: 75.69
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+ name: accuracy
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+ source:
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+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rhysjones/phi-2-orange-v2
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+ name: Open LLM Leaderboard
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: GSM8k (5-shot)
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+ type: gsm8k
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+ config: main
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+ split: test
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+ args:
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+ num_few_shot: 5
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+ metrics:
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+ - type: acc
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+ value: 57.62
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+ name: accuracy
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+ source:
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+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rhysjones/phi-2-orange-v2
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+ name: Open LLM Leaderboard
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  ---
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+
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+ [Still uploading...]
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+
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+ This is [rhysjones/phi-2-orange-v2](https://huggingface.co/rhysjones/phi-2-orange-v2), quantized with the help of an importance matrix so it could offer better performance for being quantized, and have quantization levels available for lower-memory devices to run.
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+
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+ [Kalomaze's "groups_merged.txt"](https://github.com/ggerganov/llama.cpp/discussions/5263#discussioncomment-8395384) was used for the importance matrix, with context set to 2,048.
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+
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+ Here's a chart that provides an approximation of the HellaSwag score (out of 1,000 tasks). Thanks to the randomization of tasks, it may be slightly unprecise:
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+ |Quantization|HellaSwag|
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+ |------------|---------|
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+ |IQ1_S |32.5% |
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+ |IQ2_XXS |56.3% |
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+ |IQ2_XS |64.7% |
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+ |IQ2_S |67.0% |
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+ |Q2_K_S | |
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+ |Q2_K |69.2% |
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+ |IQ3_XXS | |
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+ |IQ3_XS | |
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+ |IQ3_S | |
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+ |IQ3_M | |
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+ |Q3_K_M |73.8% |
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+ |IQ4_XS |74.0% |
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+ |IQ4_NL |73.6% |
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+ |Q4_0 |74.1% |
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+ |Q4_K_M |74.4% |
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+ |Q5_K_M | |
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+
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+ Original model card below.
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+ ***
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+ ![Phi-2 Orange](https://huggingface.co/rhysjones/phi-2-orange-v2/resolve/main/phi-2-orange.jpg)
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+
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+ # Phi-2 Orange Version 2
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+
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+ A two-step finetune of Phi-2, with a bit more zest.
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+
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+ This is an improved version of the original [Phi-2-Orange](https://huggingface.co/rhysjones/phi-2-orange) that
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+ uses an updated training process on the same datasets.
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+
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+ It also uses the latest updated model from Microsoft's [Phi-2](https://huggingface.co/microsoft/phi-2), making it directly usable
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+ within Hugging Face's Transformers library (without the need for trust remote code).
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+
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+ # Prompt Format
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+
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+ Phi-2 Orange v2 uses ChatML as the prompt format.
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+ (Update 12th March 2024: fixed eos_token issue)
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+
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+ It's recommended to always prompt with a system instruction (use whatever system prompt you like):
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+
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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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+ ```
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+
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+ For example, if you find the model's output to be overly verbose, instruct it to be short and concise:
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+
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+ ```
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+ <|im_start|>system
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+ You are a helpful assistant. Be short and direct in your answers.<|im_end|>
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+ <|im_start|>user
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+ Was Tom Hanks in the movie Forrest Gump? If so, who did he play and give details of the plot.<|im_end|>
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+ <|im_start|>assistant
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+ ```
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+
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+ # Evaluations
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+
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+
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+ [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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+ Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_rhysjones__phi-2-orange-v2)
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+ | Metric |Value|
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+ |---------------------------------|----:|
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+ |Average |63.67|
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+ |AI2 Reasoning Challenge (25-Shot)|61.86|
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+ |HellaSwag (10-Shot) |76.32|
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+ |MMLU (5-Shot) |55.72|
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+ |TruthfulQA (0-shot) |54.84|
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+ |Winogrande (5-shot) |75.69|
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+ |GSM8k (5-shot) |57.62|
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+
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+ [YALL - Yet Another LLM Leaderboard](https://huggingface.co/spaces/mlabonne/Yet_Another_LLM_Leaderboard)
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+ Evaluation from [mlabonne](https://huggingface.co/mlabonne)'s alternative LLM leaderboard:
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+ | Metric |Value|
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+ |---------------------------------|----:|
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+ |Average |49.64|
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+ |AGIEval |34.55|
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+ |GPT4All |70.96|
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+ |TruthfulQA |54.87|
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+ |Bigbench |38.17|
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+
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+ # Limitations
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+
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+ This model shares the same limitations as the underlying Phi-2 model, details of which are found [here](https://huggingface.co/microsoft/phi-2#limitations-of-phi-2).