auto-patch README.md

README.md

@@ -18,7 +18,7 @@ quantized_by: mradermacher
 static quants of https://huggingface.co/DoeyLLM/OneLLM-Doey-ChatQA-V1-Llama-3.2-1B
 
 <!-- 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/OneLLM-Doey-ChatQA-V1-Llama-3.2-1B-i1-GGUF
 ## Usage
 
 If you are unsure how to use GGUF files, refer to one of [TheBloke's
@@ -35,10 +35,15 @@ more details, including on how to concatenate multi-part files.
 | [GGUF](https://huggingface.co/mradermacher/OneLLM-Doey-ChatQA-V1-Llama-3.2-1B-GGUF/resolve/main/OneLLM-Doey-ChatQA-V1-Llama-3.2-1B.Q3_K_S.gguf) | Q3_K_S | 0.7 |  |
 | [GGUF](https://huggingface.co/mradermacher/OneLLM-Doey-ChatQA-V1-Llama-3.2-1B-GGUF/resolve/main/OneLLM-Doey-ChatQA-V1-Llama-3.2-1B.Q3_K_M.gguf) | Q3_K_M | 0.8 | lower quality |
 | [GGUF](https://huggingface.co/mradermacher/OneLLM-Doey-ChatQA-V1-Llama-3.2-1B-GGUF/resolve/main/OneLLM-Doey-ChatQA-V1-Llama-3.2-1B.Q3_K_L.gguf) | Q3_K_L | 0.8 |  |
+| [GGUF](https://huggingface.co/mradermacher/OneLLM-Doey-ChatQA-V1-Llama-3.2-1B-GGUF/resolve/main/OneLLM-Doey-ChatQA-V1-Llama-3.2-1B.IQ4_XS.gguf) | IQ4_XS | 0.8 |  |
+| [GGUF](https://huggingface.co/mradermacher/OneLLM-Doey-ChatQA-V1-Llama-3.2-1B-GGUF/resolve/main/OneLLM-Doey-ChatQA-V1-Llama-3.2-1B.Q4_0_4_4.gguf) | Q4_0_4_4 | 0.9 | fast on arm, low quality |
 | [GGUF](https://huggingface.co/mradermacher/OneLLM-Doey-ChatQA-V1-Llama-3.2-1B-GGUF/resolve/main/OneLLM-Doey-ChatQA-V1-Llama-3.2-1B.Q4_K_S.gguf) | Q4_K_S | 0.9 | fast, recommended |
 | [GGUF](https://huggingface.co/mradermacher/OneLLM-Doey-ChatQA-V1-Llama-3.2-1B-GGUF/resolve/main/OneLLM-Doey-ChatQA-V1-Llama-3.2-1B.Q4_K_M.gguf) | Q4_K_M | 0.9 | fast, recommended |
 | [GGUF](https://huggingface.co/mradermacher/OneLLM-Doey-ChatQA-V1-Llama-3.2-1B-GGUF/resolve/main/OneLLM-Doey-ChatQA-V1-Llama-3.2-1B.Q5_K_S.gguf) | Q5_K_S | 1.0 |  |
+| [GGUF](https://huggingface.co/mradermacher/OneLLM-Doey-ChatQA-V1-Llama-3.2-1B-GGUF/resolve/main/OneLLM-Doey-ChatQA-V1-Llama-3.2-1B.Q5_K_M.gguf) | Q5_K_M | 1.0 |  |
 | [GGUF](https://huggingface.co/mradermacher/OneLLM-Doey-ChatQA-V1-Llama-3.2-1B-GGUF/resolve/main/OneLLM-Doey-ChatQA-V1-Llama-3.2-1B.Q6_K.gguf) | Q6_K | 1.1 | very good quality |
+| [GGUF](https://huggingface.co/mradermacher/OneLLM-Doey-ChatQA-V1-Llama-3.2-1B-GGUF/resolve/main/OneLLM-Doey-ChatQA-V1-Llama-3.2-1B.Q8_0.gguf) | Q8_0 | 1.4 | fast, best quality |
+| [GGUF](https://huggingface.co/mradermacher/OneLLM-Doey-ChatQA-V1-Llama-3.2-1B-GGUF/resolve/main/OneLLM-Doey-ChatQA-V1-Llama-3.2-1B.f16.gguf) | f16 | 2.6 | 16 bpw, overkill |
 
 Here is a handy graph by ikawrakow comparing some lower-quality quant
 types (lower is better):