Update VRAM table

README.md

@@ -73,22 +73,16 @@ Using <a href="https://github.com/turboderp/exllamav2/">turboderp's ExLlamaV2 v0
 
 Each branch contains an individual bits per weight, with the main one containing only the meaurement.json for further conversions.
 
-Conversion was done using the default calibration dataset.
-
-Default arguments used except when the bits per weight is above 6.0, at that point the lm_head layer is quantized at 8 bits per weight instead of the default 6.
-
 Original model: https://huggingface.co/bigcode/starcoder2-15b
 
 
-<a href="https://huggingface.co/bartowski/starcoder2-15b-exl2/tree/8_0">8.0 bits per weight</a>
-
-<a href="https://huggingface.co/bartowski/starcoder2-15b-exl2/tree/6_5">6.5 bits per weight</a>
-
-<a href="https://huggingface.co/bartowski/starcoder2-15b-exl2/tree/5_0">5.0 bits per weight</a>
-
-<a href="https://huggingface.co/bartowski/starcoder2-15b-exl2/tree/4_25">4.25 bits per weight</a>
-
-<a href="https://huggingface.co/bartowski/starcoder2-15b-exl2/tree/3_5">3.5 bits per weight</a>
+| Branch | Bits | lm_head bits | VRAM (4k) | VRAM (16k) | VRAM (32k) | Description |
+| ----- | ---- | ------- | ------ | ------ | ------ | ------------ |
+| [8_0](https://huggingface.co/bartowski/starcoder2-15b-exl2/tree/8_0) | 8.0 | 8.0 | 16.6 GB | 17.5 GB | 18.8 GB | Maximum quality that ExLlamaV2 can produce, near unquantized performance. |
+| [6_5](https://huggingface.co/bartowski/starcoder2-15b-exl2/tree/6_5) | 6.5  | 8.0 | 13.9 GB | 14.9 GB | 16.2 GB | Near unquantized performance at vastly reduced size, **recommended**. |
+| [5_0](https://huggingface.co/bartowski/starcoder2-15b-exl2/tree/5_0) | 5.0  | 6.0 | 11.2 GB | 12.2 GB | 13.5 GB | Slightly lower quality vs 6.5. |
+| [4_25](https://huggingface.co/bartowski/starcoder2-15b-exl2/tree/4_25) | 4.25 | 6.0 | 9.8 GB | 10.7 GB | 12.0 GB | GPTQ equivalent bits per weight. |
+| [3_5](https://huggingface.co/bartowski/starcoder2-15b-exl2/tree/3_5) | 3.5  | 6.0 | 8.4 GB | 9.3 GB | 10.6 GB | Lower quality, not recommended. |
 
 
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