auto-patch README.md

README.md

@@ -29,7 +29,7 @@ static quants of https://huggingface.co/inclusionAI/LLaDA-MoE-7B-A1B-Instruct
 
 ***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#LLaDA-MoE-7B-A1B-Instruct-GGUF).***
 
-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/LLaDA-MoE-7B-A1B-Instruct-i1-GGUF
 ## Usage
 
 If you are unsure how to use GGUF files, refer to one of [TheBloke's
@@ -46,10 +46,14 @@ more details, including on how to concatenate multi-part files.
 | [GGUF](https://huggingface.co/mradermacher/LLaDA-MoE-7B-A1B-Instruct-GGUF/resolve/main/LLaDA-MoE-7B-A1B-Instruct.Q3_K_S.gguf) | Q3_K_S | 3.4 |  |
 | [GGUF](https://huggingface.co/mradermacher/LLaDA-MoE-7B-A1B-Instruct-GGUF/resolve/main/LLaDA-MoE-7B-A1B-Instruct.Q3_K_M.gguf) | Q3_K_M | 3.7 | lower quality |
 | [GGUF](https://huggingface.co/mradermacher/LLaDA-MoE-7B-A1B-Instruct-GGUF/resolve/main/LLaDA-MoE-7B-A1B-Instruct.Q3_K_L.gguf) | Q3_K_L | 4.0 |  |
+| [GGUF](https://huggingface.co/mradermacher/LLaDA-MoE-7B-A1B-Instruct-GGUF/resolve/main/LLaDA-MoE-7B-A1B-Instruct.IQ4_XS.gguf) | IQ4_XS | 4.2 |  |
 | [GGUF](https://huggingface.co/mradermacher/LLaDA-MoE-7B-A1B-Instruct-GGUF/resolve/main/LLaDA-MoE-7B-A1B-Instruct.Q4_K_S.gguf) | Q4_K_S | 4.4 | fast, recommended |
 | [GGUF](https://huggingface.co/mradermacher/LLaDA-MoE-7B-A1B-Instruct-GGUF/resolve/main/LLaDA-MoE-7B-A1B-Instruct.Q4_K_M.gguf) | Q4_K_M | 4.6 | fast, recommended |
+| [GGUF](https://huggingface.co/mradermacher/LLaDA-MoE-7B-A1B-Instruct-GGUF/resolve/main/LLaDA-MoE-7B-A1B-Instruct.Q5_K_S.gguf) | Q5_K_S | 5.2 |  |
+| [GGUF](https://huggingface.co/mradermacher/LLaDA-MoE-7B-A1B-Instruct-GGUF/resolve/main/LLaDA-MoE-7B-A1B-Instruct.Q5_K_M.gguf) | Q5_K_M | 5.4 |  |
 | [GGUF](https://huggingface.co/mradermacher/LLaDA-MoE-7B-A1B-Instruct-GGUF/resolve/main/LLaDA-MoE-7B-A1B-Instruct.Q6_K.gguf) | Q6_K | 6.1 | very good quality |
 | [GGUF](https://huggingface.co/mradermacher/LLaDA-MoE-7B-A1B-Instruct-GGUF/resolve/main/LLaDA-MoE-7B-A1B-Instruct.Q8_0.gguf) | Q8_0 | 7.9 | fast, best quality |
+| [GGUF](https://huggingface.co/mradermacher/LLaDA-MoE-7B-A1B-Instruct-GGUF/resolve/main/LLaDA-MoE-7B-A1B-Instruct.f16.gguf) | f16 | 14.8 | 16 bpw, overkill |
 
 Here is a handy graph by ikawrakow comparing some lower-quality quant
 types (lower is better):