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README.md
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@@ -48,7 +48,7 @@ Each separate quant is in a different branch. See below for instructions on fet
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| Branch | Bits | Group Size | Act Order (desc_act) | File Size | ExLlama Compatible? | Made With | Description |
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| main | 4 |
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| gptq-4bit-32g-actorder_True | 4 | 32 | 1 | 38.53 GB | True | AutoGPTQ | 4-bit, with Act Order and group size. 32g gives highest possible inference quality, with maximum VRAM usage. Poor AutoGPTQ CUDA speed. |
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| gptq-4bit-64g-actorder_True | 4 | 64 | 1 | 36.00 GB | True | AutoGPTQ | 4-bit, with Act Order and group size. 64g uses less VRAM, but with slightly lower accuracy. Poor AutoGPTQ CUDA speed. |
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| gptq-4bit-128g-actorder_True | 4 | 128 | 1 | 34.73 GB | True | AutoGPTQ | 4-bit, with Act Order androup size. 128g uses even less VRAM, but with slightly lower accuracy. Poor AutoGPTQ CUDA speed. |
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| Branch | Bits | Group Size | Act Order (desc_act) | File Size | ExLlama Compatible? | Made With | Description |
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| ------ | ---- | ---------- | -------------------- | --------- | ------------------- | --------- | ----------- |
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| main | 4 | None | True | 35.74 GB | True | GPTQ-for-LLaMa | Most compatible option. Good inference speed in AutoGPTQ and GPTQ-for-LLaMa. Lower inference quality than other options. |
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| gptq-4bit-32g-actorder_True | 4 | 32 | 1 | 38.53 GB | True | AutoGPTQ | 4-bit, with Act Order and group size. 32g gives highest possible inference quality, with maximum VRAM usage. Poor AutoGPTQ CUDA speed. |
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| gptq-4bit-64g-actorder_True | 4 | 64 | 1 | 36.00 GB | True | AutoGPTQ | 4-bit, with Act Order and group size. 64g uses less VRAM, but with slightly lower accuracy. Poor AutoGPTQ CUDA speed. |
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| gptq-4bit-128g-actorder_True | 4 | 128 | 1 | 34.73 GB | True | AutoGPTQ | 4-bit, with Act Order androup size. 128g uses even less VRAM, but with slightly lower accuracy. Poor AutoGPTQ CUDA speed. |
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