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Adding Evaluation Results (#2)
Browse files- Adding Evaluation Results (a79c60cc5102075969f59803d9733633b733bc46)
Co-authored-by: Open LLM Leaderboard PR Bot <[email protected]>
README.md
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license: apache-2.0
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language:
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tags:
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base_model: JackFram/llama-160m
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datasets:
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widget:
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inference:
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parameters:
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max_new_tokens: 250
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penalty_alpha: 0.5
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top_k: 4
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repetition_penalty: 1.01
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---
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# A Llama Chat Model of 160M Parameters
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print(output[0]["generated_text"])
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```
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---
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language:
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- en
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license: apache-2.0
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tags:
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- text-generation
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base_model: JackFram/llama-160m
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datasets:
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- ehartford/wizard_vicuna_70k_unfiltered
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- totally-not-an-llm/EverythingLM-data-V3
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- Open-Orca/SlimOrca-Dedup
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- databricks/databricks-dolly-15k
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- THUDM/webglm-qa
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widget:
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- text: '<|im_start|>system
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You are a helpful assistant, who answers with empathy.<|im_end|>
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<|im_start|>user
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Got a question for you!<|im_end|>
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<|im_start|>assistant
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Sure! What''s it?<|im_end|>
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<|im_start|>user
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Why do you love cats so much!? ๐<|im_end|>
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<|im_start|>assistant'
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- text: '<|im_start|>system
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You are a helpful assistant who answers user''s questions with empathy.<|im_end|>
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<|im_start|>user
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Who is Mona Lisa?<|im_end|>
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<|im_start|>assistant'
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- text: '<|im_start|>system
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You are a helpful assistant who provides concise responses.<|im_end|>
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<|im_start|>user
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Heya!<|im_end|>
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<|im_start|>assistant
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Hi! How may I help you today?<|im_end|>
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<|im_start|>user
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I need to build a simple website. Where should I start learning about web development?<|im_end|>
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<|im_start|>assistant'
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- text: '<|im_start|>user
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Invited some friends to come home today. Give me some ideas for games to play
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with them!<|im_end|>
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<|im_start|>assistant'
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- text: '<|im_start|>system
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You are a helpful assistant who answers user''s questions with details and curiosity.<|im_end|>
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<|im_start|>user
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What are some potential applications for quantum computing?<|im_end|>
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<|im_start|>assistant'
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- text: '<|im_start|>system
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You are a helpful assistant who gives creative responses.<|im_end|>
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<|im_start|>user
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Write the specs of a game about mages in a fantasy world.<|im_end|>
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<|im_start|>assistant'
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- text: '<|im_start|>system
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You are a helpful assistant who answers user''s questions with details.<|im_end|>
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<|im_start|>user
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Tell me about the pros and cons of social media.<|im_end|>
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<|im_start|>assistant'
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- text: '<|im_start|>system
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You are a helpful assistant who answers user''s questions with confidence.<|im_end|>
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<|im_start|>user
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What is a dog?<|im_end|>
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<|im_start|>assistant
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A dog is a four-legged, domesticated animal that is a member of the class Mammalia,
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which includes all mammals. Dogs are known for their loyalty, playfulness, and
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ability to be trained for various tasks. They are also used for hunting, herding,
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and as service animals.<|im_end|>
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<|im_start|>user
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What is the color of an apple?<|im_end|>
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<|im_start|>assistant'
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inference:
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parameters:
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max_new_tokens: 250
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penalty_alpha: 0.5
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top_k: 4
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repetition_penalty: 1.01
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model-index:
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- name: Llama-160M-Chat-v1
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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: 24.74
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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=Felladrin/Llama-160M-Chat-v1
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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: 35.29
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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=Felladrin/Llama-160M-Chat-v1
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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: 26.13
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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=Felladrin/Llama-160M-Chat-v1
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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: 44.16
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Felladrin/Llama-160M-Chat-v1
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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: 51.3
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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=Felladrin/Llama-160M-Chat-v1
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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: 0.0
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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=Felladrin/Llama-160M-Chat-v1
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name: Open LLM Leaderboard
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---
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# A Llama Chat Model of 160M Parameters
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print(output[0]["generated_text"])
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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_Felladrin__Llama-160M-Chat-v1)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |30.27|
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|AI2 Reasoning Challenge (25-Shot)|24.74|
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|HellaSwag (10-Shot) |35.29|
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|MMLU (5-Shot) |26.13|
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|TruthfulQA (0-shot) |44.16|
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|Winogrande (5-shot) |51.30|
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|GSM8k (5-shot) | 0.00|
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