BoltMonkey
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Adding Evaluation Results
Browse filesThis is an automated PR created with https://huggingface.co/spaces/Weyaxi/open-llm-leaderboard-results-pr
The purpose of this PR is to add evaluation results from the Open LLM Leaderboard to your model card.
If you encounter any issues, please report them to https://huggingface.co/spaces/Weyaxi/open-llm-leaderboard-results-pr/discussions
README.md
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---
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base_model:
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- mlabonne/NeuralDaredevil-8B-abliterated
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- grimjim/Llama-3.1-SuperNova-Lite-lorabilterated-8B
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tags:
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- merge
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- mergekit
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- lazymergekit
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- mlabonne/NeuralDaredevil-8B-abliterated
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- grimjim/Llama-3.1-SuperNova-Lite-lorabilterated-8B
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---
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# NeuralDaredevil-SuperNova-Lite-7B-DARETIES-abliterated
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@@ -59,4 +154,17 @@ pipeline = transformers.pipeline(
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outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
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print(outputs[0]["generated_text"])
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-
```
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---
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tags:
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- merge
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- mergekit
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- lazymergekit
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- mlabonne/NeuralDaredevil-8B-abliterated
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- grimjim/Llama-3.1-SuperNova-Lite-lorabilterated-8B
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base_model:
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- mlabonne/NeuralDaredevil-8B-abliterated
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- grimjim/Llama-3.1-SuperNova-Lite-lorabilterated-8B
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model-index:
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- name: NeuralDaredevil-SuperNova-Lite-7B-DARETIES-abliterated
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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: IFEval (0-Shot)
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type: HuggingFaceH4/ifeval
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args:
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num_few_shot: 0
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metrics:
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- type: inst_level_strict_acc and prompt_level_strict_acc
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value: 79.99
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name: strict accuracy
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=BoltMonkey/NeuralDaredevil-SuperNova-Lite-7B-DARETIES-abliterated
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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: BBH (3-Shot)
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type: BBH
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args:
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num_few_shot: 3
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metrics:
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- type: acc_norm
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value: 30.76
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=BoltMonkey/NeuralDaredevil-SuperNova-Lite-7B-DARETIES-abliterated
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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: MATH Lvl 5 (4-Shot)
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type: hendrycks/competition_math
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args:
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num_few_shot: 4
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metrics:
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- type: exact_match
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value: 10.27
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name: exact match
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=BoltMonkey/NeuralDaredevil-SuperNova-Lite-7B-DARETIES-abliterated
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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: GPQA (0-shot)
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type: Idavidrein/gpqa
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args:
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num_few_shot: 0
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metrics:
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- type: acc_norm
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value: 4.14
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name: acc_norm
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=BoltMonkey/NeuralDaredevil-SuperNova-Lite-7B-DARETIES-abliterated
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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: MuSR (0-shot)
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type: TAUR-Lab/MuSR
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args:
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num_few_shot: 0
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metrics:
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- type: acc_norm
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value: 9.47
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name: acc_norm
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=BoltMonkey/NeuralDaredevil-SuperNova-Lite-7B-DARETIES-abliterated
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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-PRO (5-shot)
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type: TIGER-Lab/MMLU-Pro
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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: 30.37
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name: accuracy
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=BoltMonkey/NeuralDaredevil-SuperNova-Lite-7B-DARETIES-abliterated
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name: Open LLM Leaderboard
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---
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# NeuralDaredevil-SuperNova-Lite-7B-DARETIES-abliterated
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outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
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print(outputs[0]["generated_text"])
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```
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_BoltMonkey__NeuralDaredevil-SuperNova-Lite-7B-DARETIES-abliterated)
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| Metric |Value|
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|-------------------|----:|
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|Avg. |27.50|
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|IFEval (0-Shot) |79.99|
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|BBH (3-Shot) |30.76|
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|MATH Lvl 5 (4-Shot)|10.27|
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|GPQA (0-shot) | 4.14|
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|MuSR (0-shot) | 9.47|
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|MMLU-PRO (5-shot) |30.37|
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