RichardErkhov/R136a1_-_InfinityKumon-2x7B-gguf

Quantization made by Richard Erkhov.

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InfinityKumon-2x7B - GGUF

• Model creator: https://huggingface.co/R136a1/
• Original model: https://huggingface.co/R136a1/InfinityKumon-2x7B/

Name	Quant method	Size
InfinityKumon-2x7B.Q2_K.gguf	Q2_K	4.43GB
InfinityKumon-2x7B.IQ3_XS.gguf	IQ3_XS	4.95GB
InfinityKumon-2x7B.IQ3_S.gguf	IQ3_S	5.22GB
InfinityKumon-2x7B.Q3_K_S.gguf	Q3_K_S	5.2GB
InfinityKumon-2x7B.IQ3_M.gguf	IQ3_M	5.35GB
InfinityKumon-2x7B.Q3_K.gguf	Q3_K	5.78GB
InfinityKumon-2x7B.Q3_K_M.gguf	Q3_K_M	5.78GB
InfinityKumon-2x7B.Q3_K_L.gguf	Q3_K_L	6.27GB
InfinityKumon-2x7B.IQ4_XS.gguf	IQ4_XS	6.5GB
InfinityKumon-2x7B.Q4_0.gguf	Q4_0	6.78GB
InfinityKumon-2x7B.IQ4_NL.gguf	IQ4_NL	6.85GB
InfinityKumon-2x7B.Q4_K_S.gguf	Q4_K_S	6.84GB
InfinityKumon-2x7B.Q4_K.gguf	Q4_K	7.25GB
InfinityKumon-2x7B.Q4_K_M.gguf	Q4_K_M	7.25GB
InfinityKumon-2x7B.Q4_1.gguf	Q4_1	7.52GB
InfinityKumon-2x7B.Q5_0.gguf	Q5_0	8.26GB
InfinityKumon-2x7B.Q5_K_S.gguf	Q5_K_S	8.26GB
InfinityKumon-2x7B.Q5_K.gguf	Q5_K	8.51GB
InfinityKumon-2x7B.Q5_K_M.gguf	Q5_K_M	8.51GB
InfinityKumon-2x7B.Q5_1.gguf	Q5_1	9.01GB
InfinityKumon-2x7B.Q6_K.gguf	Q6_K	9.84GB
InfinityKumon-2x7B.Q8_0.gguf	Q8_0	12.75GB

Original model description:

language: - en base_model: - Endevor/InfinityRP-v1-7B - grimjim/kukulemon-7B license: apache-2.0 tags: - safetensors - mixtral - not-for-all-audiences - nsfw model-index: - name: InfinityKumon-2x7B results: - task: type: text-generation name: Text Generation dataset: name: AI2 Reasoning Challenge (25-Shot) type: ai2_arc config: ARC-Challenge split: test args: num_few_shot: 25 metrics: - type: acc_norm value: 69.62 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=R136a1/InfinityKumon-2x7B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: HellaSwag (10-Shot) type: hellaswag split: validation args: num_few_shot: 10 metrics: - type: acc_norm value: 87.09 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=R136a1/InfinityKumon-2x7B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MMLU (5-Shot) type: cais/mmlu config: all split: test args: num_few_shot: 5 metrics: - type: acc value: 64.97 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=R136a1/InfinityKumon-2x7B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: TruthfulQA (0-shot) type: truthful_qa config: multiple_choice split: validation args: num_few_shot: 0 metrics: - type: mc2 value: 61.99 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=R136a1/InfinityKumon-2x7B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: Winogrande (5-shot) type: winogrande config: winogrande_xl split: validation args: num_few_shot: 5 metrics: - type: acc value: 81.93 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=R136a1/InfinityKumon-2x7B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: GSM8k (5-shot) type: gsm8k config: main split: test args: num_few_shot: 5 metrics: - type: acc value: 63.53 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=R136a1/InfinityKumon-2x7B name: Open LLM Leaderboard

InfinityKumon-2x7B

Another MoE merge from Endevor/InfinityRP-v1-7B and grimjim/kukulemon-7B.

The reason? Because I like InfinityRP-v1-7B so much and wondering if I can improve it even more by merging 2 great models into MoE.

Prompt format:

Alpaca or ChatML

Switch: FP16 - GGUF

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	71.52
AI2 Reasoning Challenge (25-Shot)	69.62
HellaSwag (10-Shot)	87.09
MMLU (5-Shot)	64.97
TruthfulQA (0-shot)	61.99
Winogrande (5-shot)	81.93
GSM8k (5-shot)	63.53