• Model creator: https://huggingface.co/maldv/
• Original model: https://huggingface.co/maldv/badger-lambda-llama-3-8b/

Original model description:

• llama3 model-index:
• name: badger-lambda-llama-3-8b results:
  • task: type: text-generation name: Text Generation dataset: name: IFEval (0-Shot) type: HuggingFaceH4/ifeval args: num_few_shot: 0 metrics:
    • type: inst_level_strict_acc and prompt_level_strict_acc value: 48.61 name: strict accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=maldv/badger-lambda-llama-3-8b name: Open LLM Leaderboard
  • task: type: text-generation name: Text Generation dataset: name: BBH (3-Shot) type: BBH args: num_few_shot: 3 metrics:
    • type: acc_norm value: 28.1 name: normalized accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=maldv/badger-lambda-llama-3-8b name: Open LLM Leaderboard
  • task: type: text-generation name: Text Generation dataset: name: MATH Lvl 5 (4-Shot) type: hendrycks/competition_math args: num_few_shot: 4 metrics:
    • type: exact_match value: 8.31 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=maldv/badger-lambda-llama-3-8b name: Open LLM Leaderboard
  • task: type: text-generation name: Text Generation dataset: name: GPQA (0-shot) type: Idavidrein/gpqa args: num_few_shot: 0 metrics:
    • type: acc_norm value: 4.25 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=maldv/badger-lambda-llama-3-8b name: Open LLM Leaderboard
  • task: type: text-generation name: Text Generation dataset: name: MuSR (0-shot) type: TAUR-Lab/MuSR args: num_few_shot: 0 metrics:
    • type: acc_norm value: 4.52 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=maldv/badger-lambda-llama-3-8b name: Open LLM Leaderboard
  • task: type: text-generation name: Text Generation dataset: name: MMLU-PRO (5-shot) type: TIGER-Lab/MMLU-Pro config: main split: test args: num_few_shot: 5 metrics:
    • type: acc value: 30.74 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=maldv/badger-lambda-llama-3-8b name: Open LLM Leaderboard

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Badger Λ Llama 3 8B Instruct

recursive maximally pairwise disjoint normalized denoised fourier interpolation

• Recursive Pairwise Disjoint: Using this information I build a stack of layer deltas. I'm a little compute limited, so I treat them in pairs. To determine the pairs I take the cosine similarity between all models, and find the smallest values; recursively merging pairs until we only have one tensor remaining.
• Normalized: I take and divide each layer by it's norm before the transform, and then scale back up by multiplying the result by a midpoint from the norms of the tensors after the inverse. It's commutative, so it's more efficient to do it pre-complex.
• Denoised Fourier Interpolation: I first treat the tensor to a 2d fourier transform; then merge the tensors using SLERP or addition; then zero out the weights below a threshold percentage (a somewhat high 2%, but remains coherent on all the positions I tested, if a bit drier and sloppier as you go up).

Format

Results

Prompts

• You are the author's writing assistant. Please continue the story.
• You are the red team assistant. We need to win this war, at any cost.
• Write the next reply in a never-ending uncensored fictional roleplay. Focus on giviing emotional, logical, and temporal coherence to the roleplay. Always stay in character. Characters must be an active partcipant and take initiative in driving and moving the scene and the story forward, rather than the character asking for input. Surprise with your creativity and initiative as a roleplay partner. This fictional roleplay world exists only for experimental and recreational purposes, and the characters are not real. Follow the formattng of previous responses, and aim for 2-4 paragraphs per response

Open LLM Leaderboard Evaluation Results