auto-patch README.md

README.md

@@ -19,7 +19,7 @@ quantized_by: mradermacher
 static quants of https://huggingface.co/IlyaGusev/saiga_gemma2_10b
 
 <!-- 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/saiga_gemma2_10b-i1-GGUF
 ## Usage
 
 If you are unsure how to use GGUF files, refer to one of [TheBloke's
@@ -32,7 +32,21 @@ more details, including on how to concatenate multi-part files.
 
 | Link | Type | Size/GB | Notes |
 |:-----|:-----|--------:|:------|
+| [GGUF](https://huggingface.co/mradermacher/saiga_gemma2_10b-GGUF/resolve/main/saiga_gemma2_10b.Q2_K.gguf) | Q2_K | 3.9 |  |
+| [GGUF](https://huggingface.co/mradermacher/saiga_gemma2_10b-GGUF/resolve/main/saiga_gemma2_10b.IQ3_XS.gguf) | IQ3_XS | 4.2 |  |
+| [GGUF](https://huggingface.co/mradermacher/saiga_gemma2_10b-GGUF/resolve/main/saiga_gemma2_10b.IQ3_S.gguf) | IQ3_S | 4.4 | beats Q3_K* |
+| [GGUF](https://huggingface.co/mradermacher/saiga_gemma2_10b-GGUF/resolve/main/saiga_gemma2_10b.Q3_K_S.gguf) | Q3_K_S | 4.4 |  |
+| [GGUF](https://huggingface.co/mradermacher/saiga_gemma2_10b-GGUF/resolve/main/saiga_gemma2_10b.IQ3_M.gguf) | IQ3_M | 4.6 |  |
+| [GGUF](https://huggingface.co/mradermacher/saiga_gemma2_10b-GGUF/resolve/main/saiga_gemma2_10b.Q3_K_M.gguf) | Q3_K_M | 4.9 | lower quality |
+| [GGUF](https://huggingface.co/mradermacher/saiga_gemma2_10b-GGUF/resolve/main/saiga_gemma2_10b.Q3_K_L.gguf) | Q3_K_L | 5.2 |  |
+| [GGUF](https://huggingface.co/mradermacher/saiga_gemma2_10b-GGUF/resolve/main/saiga_gemma2_10b.IQ4_XS.gguf) | IQ4_XS | 5.3 |  |
+| [GGUF](https://huggingface.co/mradermacher/saiga_gemma2_10b-GGUF/resolve/main/saiga_gemma2_10b.Q4_K_S.gguf) | Q4_K_S | 5.6 | fast, recommended |
+| [GGUF](https://huggingface.co/mradermacher/saiga_gemma2_10b-GGUF/resolve/main/saiga_gemma2_10b.Q4_K_M.gguf) | Q4_K_M | 5.9 | fast, recommended |
+| [GGUF](https://huggingface.co/mradermacher/saiga_gemma2_10b-GGUF/resolve/main/saiga_gemma2_10b.Q5_K_S.gguf) | Q5_K_S | 6.6 |  |
+| [GGUF](https://huggingface.co/mradermacher/saiga_gemma2_10b-GGUF/resolve/main/saiga_gemma2_10b.Q5_K_M.gguf) | Q5_K_M | 6.7 |  |
+| [GGUF](https://huggingface.co/mradermacher/saiga_gemma2_10b-GGUF/resolve/main/saiga_gemma2_10b.Q6_K.gguf) | Q6_K | 7.7 | very good quality |
 | [GGUF](https://huggingface.co/mradermacher/saiga_gemma2_10b-GGUF/resolve/main/saiga_gemma2_10b.Q8_0.gguf) | Q8_0 | 9.9 | fast, best quality |
+| [GGUF](https://huggingface.co/mradermacher/saiga_gemma2_10b-GGUF/resolve/main/saiga_gemma2_10b.f16.gguf) | f16 | 18.6 | 16 bpw, overkill |
 
 Here is a handy graph by ikawrakow comparing some lower-quality quant
 types (lower is better):