auto-patch README.md

README.md

@@ -37,7 +37,7 @@ quantized_by: mradermacher
 static quants of https://huggingface.co/CohereForAI/aya-23-8B
 
 <!-- provided-files -->
-weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
+weighted/imatrix quants are available at https://huggingface.co/mradermacher/aya-23-8B-i1-GGUF
 ## Usage
 
 If you are unsure how to use GGUF files, refer to one of [TheBloke's
@@ -50,7 +50,21 @@ more details, including on how to concatenate multi-part files.
 
 | Link | Type | Size/GB | Notes |
 |:-----|:-----|--------:|:------|
+| [GGUF](https://huggingface.co/mradermacher/aya-23-8B-GGUF/resolve/main/aya-23-8B.Q2_K.gguf) | Q2_K | 3.5 |  |
+| [GGUF](https://huggingface.co/mradermacher/aya-23-8B-GGUF/resolve/main/aya-23-8B.IQ3_XS.gguf) | IQ3_XS | 3.8 |  |
+| [GGUF](https://huggingface.co/mradermacher/aya-23-8B-GGUF/resolve/main/aya-23-8B.Q3_K_S.gguf) | Q3_K_S | 4.0 |  |
+| [GGUF](https://huggingface.co/mradermacher/aya-23-8B-GGUF/resolve/main/aya-23-8B.IQ3_S.gguf) | IQ3_S | 4.0 | beats Q3_K* |
+| [GGUF](https://huggingface.co/mradermacher/aya-23-8B-GGUF/resolve/main/aya-23-8B.IQ3_M.gguf) | IQ3_M | 4.1 |  |
+| [GGUF](https://huggingface.co/mradermacher/aya-23-8B-GGUF/resolve/main/aya-23-8B.Q3_K_M.gguf) | Q3_K_M | 4.3 | lower quality |
+| [GGUF](https://huggingface.co/mradermacher/aya-23-8B-GGUF/resolve/main/aya-23-8B.Q3_K_L.gguf) | Q3_K_L | 4.6 |  |
+| [GGUF](https://huggingface.co/mradermacher/aya-23-8B-GGUF/resolve/main/aya-23-8B.IQ4_XS.gguf) | IQ4_XS | 4.7 |  |
+| [GGUF](https://huggingface.co/mradermacher/aya-23-8B-GGUF/resolve/main/aya-23-8B.Q4_K_S.gguf) | Q4_K_S | 4.9 | fast, recommended |
+| [GGUF](https://huggingface.co/mradermacher/aya-23-8B-GGUF/resolve/main/aya-23-8B.Q4_K_M.gguf) | Q4_K_M | 5.2 | fast, recommended |
+| [GGUF](https://huggingface.co/mradermacher/aya-23-8B-GGUF/resolve/main/aya-23-8B.Q5_K_S.gguf) | Q5_K_S | 5.8 |  |
+| [GGUF](https://huggingface.co/mradermacher/aya-23-8B-GGUF/resolve/main/aya-23-8B.Q5_K_M.gguf) | Q5_K_M | 5.9 |  |
+| [GGUF](https://huggingface.co/mradermacher/aya-23-8B-GGUF/resolve/main/aya-23-8B.Q6_K.gguf) | Q6_K | 6.7 | very good quality |
 | [GGUF](https://huggingface.co/mradermacher/aya-23-8B-GGUF/resolve/main/aya-23-8B.Q8_0.gguf) | Q8_0 | 8.6 | fast, best quality |
+| [GGUF](https://huggingface.co/mradermacher/aya-23-8B-GGUF/resolve/main/aya-23-8B.f16.gguf) | f16 | 16.2 | 16 bpw, overkill |
 
 Here is a handy graph by ikawrakow comparing some lower-quality quant
 types (lower is better):