Update README.md

README.md

@@ -34,12 +34,42 @@ The vitormesaque/irisk dataset was obtained through the knowledge base of the MA
 
 ## Model Usage
 
+
 ### How to Get Started with the Model
 
 Use the code below to get started with the model:
 
+```python
+
+# Load model directly
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+tokenizer = AutoTokenizer.from_pretrained("vitormesaque/i-llama")
+model = AutoModelForCausalLM.from_pretrained("vitormesaque/i-llama")
+
+```
+## Usage
+
+```python
 
 
+FastLanguageModel.for_inference(model) # Enable native 2x faster inference
+inputs = tokenizer(
+[
+    irisk_prompt.format(
+        "Extract issues from the user review in JSON format. For each issue, provide label, functionality, severity (1-5), likelihood (1-5), category (Bug, User Experience, Performance, Security, Compatibility, Functionality, UI, Connectivity, Localization, Accessibility, Data Handling, Privacy, Notifications, Account Management, Payment, Content Quality, Support, Updates, Syncing, Customization), and the sentence.", # instruction
+        "I used to love this app, but now it's become frustrating as hell. We can't see lyrics, we can't CHOOSE WHAT SONG WE WANT TO LISTEN TO, we can't skip a song more than a few times, there are ads after every two songs, and all in all it's a horrible overrated app. If I could give this 0 stars, I would.", # input
+        "", # output - leave this blank for generation!
+    )
+], return_tensors = "pt").to("cuda")
+
+
+from transformers import TextStreamer
+text_streamer = TextStreamer(tokenizer)
+_ = model.generate(**inputs, streamer = text_streamer, max_new_tokens = 512)
+
+
+```
 ### Evaluation
 
 The model was evaluated using a separate portion of the vitormesaque/irisk dataset.