Upload complete model

README.md

@@ -9,7 +9,7 @@ tags:
 ---
 **See Kimi-K2 Dynamic MLX in action - [https://youtu.be/-zfUvA2CDqE](https://youtu.be/-zfUvA2CDqE)**
 
-*q3.95bit dynamic quant achieves 1.243 perplexity in our testing, slotting closer to q4 perplexity (1.168) than q3 perplexity (1.900).*
+*q3.95bit dynamic quant typically achieves 1.243 perplexity in our testing, slotting closer to q4 perplexity (1.168) than q3 perplexity (1.900).*
 | Quantization | Perplexity |
 |:------------:|:----------:|
 | **q2**       | 41.293     |
@@ -21,10 +21,10 @@ tags:
 
 ## Usage Notes
 
-* Built with a modified version of [MLX](https://github.com/ml-explore/mlx) 0.26
-* Runs on a single M3 Ultra 512GB RAM
+* Runs on a single M3 Ultra 512GB RAM using [Inferencer app](https://inferencer.com)
 * Requires expanding VRAM limit to at least ~500000 MB
   * For a larger context window, 507000 is used in VRAM limit command below.
   * `sudo sysctl iogpu.wired_limit_mb=507000`
 * Expect ~20 tokens/s
+* Quantized with a modified version of [MLX](https://github.com/ml-explore/mlx) 0.26
 * For more details see [demonstration video](https://youtu.be/-zfUvA2CDqE) or visit [Kimi K2](https://moonshotai.github.io/Kimi-K2/).