RichardErkhov
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README.md
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Quantization made by Richard Erkhov.
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[Github](https://github.com/RichardErkhov)
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[Discord](https://discord.gg/pvy7H8DZMG)
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[Request more models](https://github.com/RichardErkhov/quant_request)
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Fireball-Alpaca-Llama3.1.07-8B-Philos-Math-KTO-beta - bnb 4bits
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- Model creator: https://huggingface.co/EpistemeAI/
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- Original model: https://huggingface.co/EpistemeAI/Fireball-Alpaca-Llama3.1.07-8B-Philos-Math-KTO-beta/
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Original model description:
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---
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language:
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- en
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widget:
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- text: "My name is Julien and I like to"
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example_title: "Julien"
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- text: "My name is Merve and my favorite"
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example_title: "Merve"
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license: apache-2.0
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tags:
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- text-generation-inference
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- transformers
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- unsloth
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- llama
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- trl
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base_model: EpistemeAI2/Fireball-Alpaca-Llama3.1.07-8B-Philos-Math
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model-index:
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- name: Fireball-Alpaca-Llama3.1.07-8B-Philos-Math-KTO-beta
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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: 72.74
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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=EpistemeAI/Fireball-Alpaca-Llama3.1.07-8B-Philos-Math-KTO-beta
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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: 26.9
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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=EpistemeAI/Fireball-Alpaca-Llama3.1.07-8B-Philos-Math-KTO-beta
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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: 13.22
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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=EpistemeAI/Fireball-Alpaca-Llama3.1.07-8B-Philos-Math-KTO-beta
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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: 4.03
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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=EpistemeAI/Fireball-Alpaca-Llama3.1.07-8B-Philos-Math-KTO-beta
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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: 4.28
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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=EpistemeAI/Fireball-Alpaca-Llama3.1.07-8B-Philos-Math-KTO-beta
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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: 28.26
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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=EpistemeAI/Fireball-Alpaca-Llama3.1.07-8B-Philos-Math-KTO-beta
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name: Open LLM Leaderboard
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---
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# KTO Fine tuning!
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A [**KTO**](https://arxiv.org/abs/2402.01306) version EpistemeAI2/Fireball-Alpaca-Llama3.1.07-8B-Philos-Math
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# Uploaded model
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- **Developed by:** EpistemeAI2
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- **License:** apache-2.0
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- **Finetuned from model :** EpistemeAI2/Fireball-Alpaca-Llama3.1.07-8B-Philos-Math
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This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
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[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
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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_EpistemeAI__Fireball-Alpaca-Llama3.1.07-8B-Philos-Math-KTO-beta)
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| Metric |Value|
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|-------------------|----:|
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|Avg. |24.90|
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|IFEval (0-Shot) |72.74|
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|BBH (3-Shot) |26.90|
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|MATH Lvl 5 (4-Shot)|13.22|
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|GPQA (0-shot) | 4.03|
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|MuSR (0-shot) | 4.28|
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|MMLU-PRO (5-shot) |28.26|
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