Update README.md

README.md

@@ -1,5 +1,5 @@
 ---
-library_name: peft
+library_name: transformers
 base_model: codellama/CodeLlama-7b-Instruct-hf
 license: apache-2.0
 datasets:
@@ -42,6 +42,64 @@ Input : Text
 
 Output : Text (Code)
 
+
+**Usage**
+
+Using Transformers
+```python
+#Import required libraries
+import torch
+from transformers import (
+    AutoModelForCausalLM,
+    AutoTokenizer
+)
+
+#Load Model
+model_name = "semantixai/LloroV2"
+base_model = AutoModelForCausalLM.from_pretrained(
+        model_name,
+        return_dict=True,
+        torch_dtype=torch.float16,
+        device_map="auto",
+    )
+
+#Load Tokenizer
+tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
+
+
+#Define Prompt
+user_prompt = "Desenvolva um algoritmo em Python para calcular a média e a mediana dos preços de vendas por tipo de material do produto."
+system = "Provide answers in Python without explanations, only the code"
+prompt_template = f"[INST] <<SYS>>\\n{system}\\n<</SYS>>\\n\\n{user_prompt}[/INST]"
+
+#Call the model
+input_ids = tokenizer([prompt_template], return_tensors="pt")["input_ids"].to("cuda")
+
+            
+outputs = base_model.generate(
+    input_ids,
+    do_sample=True,
+    top_p=0.95,
+    max_new_tokens=1024,
+    temperature=0.1,
+    )
+
+#Decode and retrieve Output
+output_text = tokenizer.batch_decode(outputs, skip_prompt=True, skip_special_tokens=False)
+display(output_text)
+```
+
+Using an OpenAI compatible inference server (like [vLLM](https://docs.vllm.ai/en/latest/index.html))
+```python
+from openai import OpenAI
+
+client = OpenAI(
+    api_key="EMPTY",
+    base_url="http://localhost:8000/v1",
+)
+user_prompt = "Desenvolva um algoritmo em Python para calcular a média e a mediana dos preços de vendas por tipo de material do produto."
+completion = client.chat.completions.create(temperature=0.1,frequency_penalty=0.1,model="semantixai/LloroV2",messages=[{"role":"system","content":"Provide answers in Python without explanations, only the code"},{"role":"user","content":user_prompt}])
+```
  
 
 **Params**