Update README.md

README.md

@@ -9,6 +9,25 @@ tags:
 This model was converted to GGUF format from [`Pinkstack/Superthoughts-lite-v2-MOE-Llama3.2-experimental-0427`](https://huggingface.co/Pinkstack/Superthoughts-lite-v2-MOE-Llama3.2-experimental-0427) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
 Refer to the [original model card](https://huggingface.co/Pinkstack/Superthoughts-lite-v2-MOE-Llama3.2-experimental-0427) for more details on the model.
 
+## ⚠️THIS MODEL IS EXPERIMENTAL!!
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/6710ba6af1279fe0dfe33afe/zeYeNGUPCXFPUodR2Gj8u.png)
+After more than two months since the release of superthoughts lite v1, we finally release the new version. **v2**
+Unlike the first generation of superthoughts lite, this model is a MoE (Mixture of experts), of 4 special fine-tuned experts based off of llama-3.2-1B models.
+# Information
+- In GGUF Q8_0, the model runs at ~8 tokens per second on a Snapdragon 8 Gen 2 with 12GB of ram, which is faster than Pinkstack/PARM-V2-QwQ-Qwen-2.5-o1-3B-GGUF (which runs at ~5 tokens a second).
+- The chat expert was fine tuned on 23 different languages for 2 epochs, but the model should still only be used for english-to-english generation.
+- This model has a total of 3.91B parameters, and 2 experts are active with each token. There is an expert for math, code, general conversations and medical situations.
+- Long context: the model supports up to **131,072** input tokens, and can generate up to **16,384** tokens.
+- To enable proper reasoning, set this as the system prompt:
+```
+You are Superthoughts lite v2 by Pinkstack, which thinks before answering user questions. always respond in the following format:\n<think>\n(Your thinking process\n</think>\n(Your final output).
+```
+⚠️ Due to the nature of an experimental model, it may fall into reasoning loops; users are responsible for all outputs from this model.
+This experimental model is more of a proof-of-concept for now. It fully works and it has some pretty nice performance, for having less than 2 billion parameters activated per token.
+
+**If you have any questions, feel free to open a "New Discussion".**
+
 ## Use with llama.cpp
 Install llama.cpp through brew (works on Mac and Linux)
 
@@ -27,24 +46,3 @@ llama-cli --hf-repo Pinkstack/Superthoughts-lite-v2-MOE-Llama3.2-experimental-04
 ```bash
 llama-server --hf-repo Pinkstack/Superthoughts-lite-v2-MOE-Llama3.2-experimental-0427-Q8_0-GGUF --hf-file superthoughts-lite-v2-moe-llama3.2-experimental-0427-q8_0.gguf -c 2048
 ```
-
-Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.
-
-Step 1: Clone llama.cpp from GitHub.
-```
-git clone https://github.com/ggerganov/llama.cpp
-```
-
-Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
-```
-cd llama.cpp && LLAMA_CURL=1 make
-```
-
-Step 3: Run inference through the main binary.
-```
-./llama-cli --hf-repo Pinkstack/Superthoughts-lite-v2-MOE-Llama3.2-experimental-0427-Q8_0-GGUF --hf-file superthoughts-lite-v2-moe-llama3.2-experimental-0427-q8_0.gguf -p "The meaning to life and the universe is"
-```
-or 
-```
-./llama-server --hf-repo Pinkstack/Superthoughts-lite-v2-MOE-Llama3.2-experimental-0427-Q8_0-GGUF --hf-file superthoughts-lite-v2-moe-llama3.2-experimental-0427-q8_0.gguf -c 2048
-```