Update README.md

README.md

@@ -110,24 +110,22 @@ This is the model card of a 🤗 transformers model that has been pushed on the
 ## Uses
 
 ```py
-# Load the model
-model = LlamaForCausalLM.from_pretrained('/content/kongo-llama/checkpoint-9000')
-
-# Prepare input text
-text = "Nzambi "
-inputs = wrapped_tokenizer(text, return_tensors="pt")
-
-# Generate text
-generated_ids = model.generate(
-    max_length=150,  # Increased length
-    num_beams=5,      # Use beam search
-    temperature=0.7,  # Adjust temperature for creativity
-    do_sample=True,
-    top_k=50,         # Limit vocabulary for next token
-    top_p=0.95        # Nucleus sampling
+# Use a pipeline as a high-level helper
+from transformers import pipeline
+pipe = pipeline("text-generation", model="Svngoku/kongo-llama")
+
+pipe(
+  "Mbote, mono ",     
+  max_length=150, 
+  num_beams=5,     
+  temperature=0.7, 
+  do_sample=True,
+  top_p=0.95 
 )
 
-# Decode and print the generated text
-generated_text = wrapped_tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
-print(generated_text)
+```
+
+```sh
+[{'generated_text': 'Mbote, mono  na ngambu ya mpila ya bo ke monisa nde bantu yonso zole yina kaka na kati ya bo ke sadilaka yo mosi ve kana bo ke vandaka ti yo yina, to bima ya nkaka ya bo ke salaka sambu na bana ya zulu.'}]
+
 ```