Update README.md

README.md

@@ -77,7 +77,43 @@ inputs = tokenizer(prompt, return_tensors="pt", return_attention_mask=False).to(
 # Here comes the fun part!  Let's unleash the power of HelpingAI-3B to generate some awesome text
 generated_text = model.generate(**inputs, max_length=3084, top_p=0.95, do_sample=True, temperature=0.6, use_cache=True, streamer=streamer)
 ```
+*Directly using this model from GGUF*
 
+```python
+%pip install -U 'webscout[local]'
+
+from webscout.Local.utils import download_model
+from webscout.Local.model import Model
+from webscout.Local.thread import Thread
+from webscout.Local import formats
+from webscout.Local.samplers import SamplerSettings
+
+
+# 1. Download the model
+repo_id = "OEvortex/HelpingAI-3B-chat" 
+filename = "helpingai-3b-chat-q4_k_m.gguf"
+model_path = download_model(repo_id, filename, token='') # Replace with your Hugging Face token also you can keep it empty
+
+# 2. Load the model 
+model = Model(model_path, n_gpu_layers=20) 
+
+# 3. Define your system prompt
+system_prompt = "You are HelpingAI a emotional AI always answer my question in HelpingAI style and to the point"
+
+# 4. Create a custom chatml format with your system prompt
+custom_chatml = formats.chatml.copy()
+custom_chatml['system_content'] = system_prompt
+
+# 5. Define your sampler settings (optional)
+sampler = SamplerSettings(temp=0.7, top_p=0.9) # Adjust these values as needed
+
+# 6. Create a Thread with the custom format and sampler
+thread = Thread(model, custom_chatml, sampler=sampler)
+
+# 7. Start interacting with the model
+thread.interact(header="🌟 HelpingAI-3B-chat: Emotionally Intelligent SLM 🚀", color=True)
+
+```
 ## Example Dialogue
   > Express joy and excitement about visiting a new place.