readme: update quant info and banner

README.md

@@ -13,7 +13,7 @@ library_name: ggml
 
 # Meta-Llama-3.1-405B-Instruct-GGUF
 
-![image/png](https://cdn-uploads.huggingface.co/production/uploads/6604e5b21eb292d6df393365/o7DiWuILyzaPLh4Ne1JKr.png)
+![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/6604e5b21eb292d6df393365/C0YBxvhqz3cqMdgfOUlUL.jpeg)
 
 Low bit quantizations of Meta's Llama 3.1 405B Instruct model. Quantized from ollama q4_0 GGUF.
 
@@ -21,15 +21,22 @@ Quantized with llama.cpp [b3449](https://github.com/ggerganov/llama.cpp/releases
 
 | Quant       | Notes                                      |
 |-------------|--------------------------------------------|
-| Q2_K        | Suitable for general inference tasks       |
-| IQ2_XXS     | Best for ultra-low memory footprint        |
-| IQ2_S       | Optimized for small VRAM environments      |
-| Q3_K_M      | Good balance between speed and accuracy    |
-| Q3_K_S      | Faster inference with minor quality loss   |
-| Q3_K_L      | High-quality with more VRAM requirement    |
-| Q4_K_M      | Superior balance, suitable for production (although this is dequanted from q4_0, don't expect higher quality)  |
-| Q4_0        | Basic quantization, good for experimentation|
-| Q4_K_S      | Fast inference, efficient for scaling      |
+| BF16        | Brain floating point, very high quality, smaller than F16 |
+| Q8_0        | 8-bit quantization, high quality, larger size |
+| Q6_K        | 6-bit quantization, very good quality-to-size ratio |
+| Q5_K        | 5-bit quantization, good balance of quality and size |
+| Q5_0        | Alternative 5-bit quantization, slightly different balance |
+| Q4_K_M      | 4-bit quantization, good for production use |
+| Q4_K_S      | 4-bit quantization, faster inference, efficient for scaling |
+| Q4_0        | Basic 4-bit quantization, good for experimentation |
+| Q3_K_L      | 3-bit quantization, high-quality with more VRAM requirement |
+| Q3_K_M      | 3-bit quantization, good balance between speed and accuracy |
+| Q3_K_S      | 3-bit quantization, faster inference with minor quality loss |
+| Q2_K        | 2-bit quantization, suitable for general inference tasks |
+| IQ2_S       | Integer 2-bit quantization, optimized for small VRAM environments |
+| IQ2_XXS     | Integer 2-bit quantization, best for ultra-low memory footprint |
+| IQ1_M       | Integer 1-bit quantization, usable
+| IQ1_S       | Integer 1-bit quantization, not recommended
 
 For higher quality quantizations (q4+), please refer to [nisten/meta-405b-instruct-cpu-optimized-gguf](https://huggingface.co/nisten/meta-405b-instruct-cpu-optimized-gguf).