Update README.md

README.md

@@ -21,32 +21,43 @@ What is the meaning of life?<|im_end|>
 <|im_start|>assistant
 ```
 
-## Training procedure
-
-### Training hyperparameters
-
-The following hyperparameters were used during training:
-- learning_rate: 2e-06
-- train_batch_size: 2
-- eval_batch_size: 2
-- seed: 42
-- distributed_type: multi-GPU
-- num_devices: 4
-- gradient_accumulation_steps: 4
-- total_train_batch_size: 32
-- total_eval_batch_size: 8
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: cosine
-- lr_scheduler_warmup_steps: 100
-- num_epochs: 1
-
-### Training results
-
-
-
-### Framework versions
-
-- Transformers 4.34.1
-- Pytorch 2.0.1+cu118
-- Datasets 2.14.6
-- Tokenizers 0.14.1
+## Examples
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+device = "cuda" # the device to load the model onto
+
+model = AutoModelForCausalLM.from_pretrained(
+    "vilm/VinaLlama2-14B",
+    torch_dtype='auto',
+    device_map="auto"
+)
+tokenizer = AutoTokenizer.from_pretrained("vilm/VinaLlama2-14B")
+
+prompt = "What is the mearning of life?"
+messages = [
+    {"role": "system", "content": "You are a helpful AI assistant."},
+    {"role": "user", "content": prompt}
+]
+text = tokenizer.apply_chat_template(
+    messages,
+    tokenize=False,
+    add_generation_prompt=True
+)
+model_inputs = tokenizer([text], return_tensors="pt").to(device)
+
+generated_ids = model.generate(
+    model_inputs.input_ids,
+    max_new_tokens=1024,
+    eos_token_id=tokenizer.eos_token_id,
+    temperature=0.25,
+)
+generated_ids = [
+    output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
+]
+
+response = tokenizer.batch_decode(generated_ids)[0]
+print(response)
+
+```