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--- |
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language: |
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- sr |
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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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- mistral |
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- gguf |
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base_model: gordicaleksa/YugoGPT |
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model_creator: Gordic Aleksa |
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model_type: mistral |
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quantized_by: datatab |
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--- |
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# YugoGPT-Quantized-GGUF |
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- **Quantized by:** datatab |
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- **License:** apache-2.0 |
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- **Author of model :** gordicaleksa/YugoGPT |
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<!-- description start --> |
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## Description |
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This repo contains GGUF format model files for [YugoGPT](https://huggingface.co/gordicaleksa/YugoGPT/). |
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<!-- description end --> |
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# Quant. preference |
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| Quant. | Description | |
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|---------------|---------------------------------------------------------------------------------------| |
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| not_quantized | Recommended. Fast conversion. Slow inference, big files. | |
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| fast_quantized| Recommended. Fast conversion. OK inference, OK file size. | |
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| quantized | Recommended. Slow conversion. Fast inference, small files. | |
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| f32 | Not recommended. Retains 100% accuracy, but super slow and memory hungry. | |
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| f16 | Fastest conversion + retains 100% accuracy. Slow and memory hungry. | |
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| q8_0 | Fast conversion. High resource use, but generally acceptable. | |
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| q4_k_m | Recommended. Uses Q6_K for half of the attention.wv and feed_forward.w2 tensors, else Q4_K | |
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| q5_k_m | Recommended. Uses Q6_K for half of the attention.wv and feed_forward.w2 tensors, else Q5_K | |
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| q2_k | Uses Q4_K for the attention.vw and feed_forward.w2 tensors, Q2_K for the other tensors.| |
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| q3_k_l | Uses Q5_K for the attention.wv, attention.wo, and feed_forward.w2 tensors, else Q3_K | |
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| q3_k_m | Uses Q4_K for the attention.wv, attention.wo, and feed_forward.w2 tensors, else Q3_K | |
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| q3_k_s | Uses Q3_K for all tensors | |
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| q4_0 | Original quant method, 4-bit. | |
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| q4_1 | Higher accuracy than q4_0 but not as high as q5_0. However has quicker inference than q5 models.| |
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| q4_k_s | Uses Q4_K for all tensors | |
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| q4_k | alias for q4_k_m | |
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| q5_k | alias for q5_k_m | |
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| q5_0 | Higher accuracy, higher resource usage and slower inference. | |
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| q5_1 | Even higher accuracy, resource usage and slower inference. | |
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| q5_k_s | Uses Q5_K for all tensors | |
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| q6_k | Uses Q8_K for all tensors | |
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| iq2_xxs | 2.06 bpw quantization | |
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| iq2_xs | 2.31 bpw quantization | |
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| iq3_xxs | 3.06 bpw quantization | |
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| q3_k_xs | 3-bit extra small quantization | |
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