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README.md
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license: other
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datasets:
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- ehartford/WizardLM_alpaca_evol_instruct_70k_unfiltered
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inference: false
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---
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## Provided files
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| Name | Quant method | Bits | Size | RAM required | Use case |
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| ---- | ---- | ---- | ---- | ---- | ----- |
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`WizardLM-30B-Uncensored.q4_0.bin` | q4_0 | 4bit |
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`WizardLM-30B-Uncensored.q4_1.bin` | q4_1 | 4bit |
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`WizardLM-30B-Uncensored.q5_0.bin` | q5_0 | 5bit | 22.4GB | 25GB | 5-bit. Higher accuracy, higher resource usage, slower inference. |
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`WizardLM-30B-Uncensored.q5_1.bin` | q5_1 | 5bit | 24.4GB | 27GB | 5-bit. Even higher accuracy and resource usage, and slower inference. |
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`WizardLM-30B-Uncensored.q8_0.bin` | q8_0 | 5bit |
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## How to run in `llama.cpp`
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license: other
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datasets:
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- ehartford/WizardLM_alpaca_evol_instruct_70k_unfiltered
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tags:
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- uncensored
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inference: false
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---
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## Provided files
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| Name | Quant method | Bits | Size | RAM required | Use case |
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| ---- | ---- | ---- | ---- | ---- | ----- |
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`WizardLM-30B-Uncensored.q4_0.bin` | q4_0 | 4bit | 18.3GB | 20GB | 4bit. |
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`WizardLM-30B-Uncensored.q4_1.bin` | q4_1 | 4bit | 20.3GB | 23GB | 4-bit. Higher accuracy than q4_0 but not as high as q5_0. However has quicker inference than q5 models. |
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`WizardLM-30B-Uncensored.q5_0.bin` | q5_0 | 5bit | 22.4GB | 25GB | 5-bit. Higher accuracy, higher resource usage, slower inference. |
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`WizardLM-30B-Uncensored.q5_1.bin` | q5_1 | 5bit | 24.4GB | 27GB | 5-bit. Even higher accuracy and resource usage, and slower inference. |
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`WizardLM-30B-Uncensored.q8_0.bin` | q8_0 | 5bit | 34.6GB | 38GB | 8-bit. Almost indistinguishable from float16. Huge resource use and slow. Not recommended for normal use.|
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## How to run in `llama.cpp`
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