Update README.md

README.md

@@ -1,29 +1,37 @@
 ---
-{}
----
----
 license: apache-2.0
+---
 
+## 🧩 Simple Use Case
 
+This section demonstrates a simple use case of how to interact with our model to solve problems in a step-by-step, friendly manner.
 
-## 🧩 Simple Use Case
+### Define the Function
 
-### define the function
+We define a function `get_completion` which takes user input, combines it with a predefined system prompt, and then sends this combined prompt to our model. The model's response is then printed out.
 
+Here's how the function is implemented:
+
+```python
+import torch                
+from transformers import pipeline   
+import os
+
+# Load model
+test_pipeline = pipeline(model="zaursamedov1/FIxtral",
+                            torch_dtype=torch.bfloat16,
+                            trust_remote_code=True,
+                            device_map="auto")
+
+### Define the function
 def get_completion(input):
-  system = "Think step by step and solve the problem in a friendly way."
-  prompt = f"#### System: {system}
-#### User: 
-{input}
-
-#### Response from My merged test model:"
-  print(prompt)
-  fixtral_prompt = test_slerp_pipeline(prompt,
-                                  max_new_tokens=500
-                                  )
-  return fixtral_prompt[0]["generated_text"]
-
-# let's prompt
+    system = "Think step by step and solve the problem in a friendly way."
+    prompt = f"#### System: {system}\\n#### User: \\n{input}\\n\\n#### Response from FIxtral model:"
+    print(prompt)
+    fixtral_prompt = test_pipeline(prompt, max_new_tokens=500)
+    return fixtral_prompt[0]["generated_text"]
+
+# Let's prompt
 prompt = "problem"
+print(get_completion(prompt))
 
-print(get_completion(prompt))