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README.md

@@ -21,10 +21,6 @@ tags:
 - lfm2
 - edge
 ---
-> [!NOTE]
->  Includes our **chat template fixes**! <br> For `llama.cpp`, use `--jinja`
->
-
 <div>
 <p style="margin-top: 0;margin-bottom: 0;">
     <em><a href="https://docs.unsloth.ai/basics/unsloth-dynamic-v2.0-gguf">Unsloth Dynamic 2.0</a> achieves superior accuracy & outperforms other leading quants.</em>
@@ -161,6 +157,10 @@ The candidate with ID 12345 is currently in the "Interview Scheduled" stage for
 
 ## 🏃 How to run LFM2
 
+You can run LFM2 with transformers and llama.cpp. vLLM support is coming.
+
+### 1. Transformers
+
 To run LFM2, you need to install Hugging Face [`transformers`](https://github.com/huggingface/transformers) from source (v4.54.0.dev0).
 You can update or install it with the following command: `pip install "transformers @ git+https://github.com/huggingface/transformers.git@main"`.
 
@@ -209,6 +209,10 @@ print(tokenizer.decode(output[0], skip_special_tokens=False))
 
 You can directly run and test the model with this [Colab notebook](https://colab.research.google.com/drive/1_q3jQ6LtyiuPzFZv7Vw8xSfPU5FwkKZY?usp=sharing).
 
+### 2. Llama.cpp
+
+You can run LFM2 with llama.cpp using its [GGUF checkpoint](https://huggingface.co/LiquidAI/LFM2-700M-GGUF). Find more information in the model card.
+
 ## 🔧 How to fine-tune LFM2
 
 We recommend fine-tuning LFM2 models on your use cases to maximize performance.