Update README.md

README.md

@@ -22,30 +22,26 @@ Using <a href="https://github.com/turboderp/exllamav2/releases/tag/v0.0.11">turb
 
 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/fblgit/UNA-dolphin-2.6-mistral-7b-dpo-laser
 
+Model Size: 7b
 
+| Branch | Bits | lm_head bits | Dataset | Size | Description |
+| ----- | ---- | ------- | ------- | ------ | ------------ |
+| [8_0](https://huggingface.co/Bartowski/UNA-dolphin-2.6-mistral-7b-dpo-laser-exl2/tree/8_0) | 8.0 | 8.0 | Default | 9.8 GB | Maximum quality that ExLlamaV2 can produce, near unquantized performance. |
+| [6_5](https://huggingface.co/Bartowski/UNA-dolphin-2.6-mistral-7b-dpo-laser-exl2/tree/6_5) | 6.5 | 8.0 | Default | 8.6 GB | Very similar to 8.0, good tradeoff of size vs performance, **recommended**. |
+| [5_0](https://huggingface.co/Bartowski/UNA-dolphin-2.6-mistral-7b-dpo-laser-exl2/tree/5_0) | 5.0 | 6.0 | Default | 7.4 GB | Slightly lower perplexity vs 6.5. |
+| [4_0](https://huggingface.co/Bartowski/UNA-dolphin-2.6-mistral-7b-dpo-laser-exl2/tree/4_0) | 4.0 | 6.0 | Default | 6.5 GB | Just under GPTQ equivalent bits per weight. |
+| [3_5](https://huggingface.co/Bartowski/UNA-dolphin-2.6-mistral-7b-dpo-laser-exl2/tree/3_5) | 3.5 | 6.0 | Default | 6.1 GB | Lower quality, only use if you have to. |
 
-<a href="https://huggingface.co/bartowski/UNA-dolphin-2.6-mistral-7b-dpo-laser-exl2/tree/8_0">8.0 bits per weight</a>
-
-<a href="https://huggingface.co/bartowski/UNA-dolphin-2.6-mistral-7b-dpo-laser-exl2/tree/6_5">6.5 bits per weight</a>
-
-<a href="https://huggingface.co/bartowski/UNA-dolphin-2.6-mistral-7b-dpo-laser-exl2/tree/5_0">5.0 bits per weight</a>
-
-<a href="https://huggingface.co/bartowski/UNA-dolphin-2.6-mistral-7b-dpo-laser-exl2/tree/4_0">4.0 bits per weight</a>
-
-<a href="https://huggingface.co/bartowski/UNA-dolphin-2.6-mistral-7b-dpo-laser-exl2/tree/3_5">3.5 bits per weight</a>
+All VRAM requirements estimated from 16k context. For 32k context add ~2 GB.
 
 ## Download instructions
 
 With git:
 
 ```shell
-git clone --single-branch --branch 4_0 https://huggingface.co/bartowski/UNA-dolphin-2.6-mistral-7b-dpo-laser-exl2
+git clone --single-branch --branch 6_5 https://huggingface.co/bartowski/UNA-dolphin-2.6-mistral-7b-dpo-laser-exl2
 ```
 
 With huggingface hub (credit to TheBloke for instructions):
@@ -64,6 +60,6 @@ huggingface-cli download bartowski/UNA-dolphin-2.6-mistral-7b-dpo-laser-exl2 --l
 To download from a different branch, add the `--revision` parameter:
 
 ```shell
-mkdir UNA-dolphin-2.6-mistral-7b-dpo-laser-exl2
-huggingface-cli download bartowski/UNA-dolphin-2.6-mistral-7b-dpo-laser-exl2 --revision 4_0 --local-dir UNA-dolphin-2.6-mistral-7b-dpo-laser-exl2 --local-dir-use-symlinks False
+mkdir UNA-dolphin-2.6-mistral-7b-dpo-laser-exl2-6_5
+huggingface-cli download bartowski/UNA-dolphin-2.6-mistral-7b-dpo-laser-exl2 --revision 6_5 --local-dir UNA-dolphin-2.6-mistral-7b-dpo-laser-exl2-6_5 --local-dir-use-symlinks False
 ```