BootsofLagrangian
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README.md
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@@ -151,8 +151,8 @@ Refer to the Provided Files table below to see what files use which methods, and
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| [AkaLlama-llama3-70b-v0.1.Q4_K_M.gguf](https://huggingface.co/mirlab/AkaLlama-llama3-70b-v0.1-GGUF/blob/main/AkaLlama-llama3-70b-v0.1.Q4_K_M.gguf) | Q4_K_M | 4 | 42.5 GB| 45.0 GB | medium, balanced quality - recommended |
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| [AkaLlama-llama3-70b-v0.1.Q5_K_S.gguf](https://huggingface.co/mirlab/AkaLlama-llama3-70b-v0.1-GGUF/blob/main/AkaLlama-llama3-70b-v0.1.Q5_K_S.gguf) | Q5_K_S | 5 | 48.7 GB| 50.2 GB | large, low quality loss - recommended |
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| [AkaLlama-llama3-70b-v0.1.Q5_K_M.gguf](https://huggingface.co/mirlab/AkaLlama-llama3-70b-v0.1-GGUF/blob/main/AkaLlama-llama3-70b-v0.1.Q5_K_M.gguf) | Q5_K_M | 5 | 50.0 GB| 52.5 GB | large, very low quality loss - recommended |
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**Note**: the above RAM figures assume no GPU offloading. If layers are offloaded to the GPU, this will reduce RAM usage and use VRAM instead.
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```
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## Evaluation
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| Model | #Parameter | Qunatized? | LogicKor |
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| [AkaLlama-llama3-70b-v0.1.Q4_K_M.gguf](https://huggingface.co/mirlab/AkaLlama-llama3-70b-v0.1-GGUF/blob/main/AkaLlama-llama3-70b-v0.1.Q4_K_M.gguf) | Q4_K_M | 4 | 42.5 GB| 45.0 GB | medium, balanced quality - recommended |
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| [AkaLlama-llama3-70b-v0.1.Q5_K_S.gguf](https://huggingface.co/mirlab/AkaLlama-llama3-70b-v0.1-GGUF/blob/main/AkaLlama-llama3-70b-v0.1.Q5_K_S.gguf) | Q5_K_S | 5 | 48.7 GB| 50.2 GB | large, low quality loss - recommended |
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| [AkaLlama-llama3-70b-v0.1.Q5_K_M.gguf](https://huggingface.co/mirlab/AkaLlama-llama3-70b-v0.1-GGUF/blob/main/AkaLlama-llama3-70b-v0.1.Q5_K_M.gguf) | Q5_K_M | 5 | 50.0 GB| 52.5 GB | large, very low quality loss - recommended |
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| AkaLlama-llama3-70b-v0.1.Q6_K.gguf | Q6_K | 6 | 54.4 GB| 59.9 GB | very large, extremely low quality loss |
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| AkaLlama-llama3-70b-v0.1.Q8_0.gguf | Q8_0 | 8 | 70.0 GB| 72.5 GB | very large, extremely low quality loss - not recommended |
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**Note**: the above RAM figures assume no GPU offloading. If layers are offloaded to the GPU, this will reduce RAM usage and use VRAM instead.
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```
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## Evaluation
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| Model | #Parameter | Qunatized? | LogicKor |
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