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RichardErkhov/R136a1_-_InfinityKumon-2x7B-gguf
R136a1_-_InfinityKumon-2x7B-gguf is a machine learning model from RichardErkhov. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Downloads · 30 days
332
9% of all-time downloads
All-time downloads
3.6K
Public
Repo size
146 GB
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0
Public
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.gguf169 GB · 100%
From the Hugging Face model README
Quantization made by Richard Erkhov.
InfinityKumon-2x7B - GGUF
| 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 |
language:

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.
Alpaca or ChatML
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 |