Update README.md

README.md

@@ -8,4 +8,34 @@ language:
 pipeline_tag: text-generation
 tags:
 - code_generation
----
+---
+
+Example inference using huggingface transformers.
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer, LlamaTokenizer
+import pandas as pd
+
+def get_prediction(raw_prediction):
+    if "[/INST]" in raw_prediction:
+        index = raw_prediction.index("[/INST]")
+        return raw_prediction[index + 7:]
+
+    return raw_prediction
+
+tokenizer = LlamaTokenizer.from_pretrained("AIAT/Pangpuriye-openthaigpt-1.0.0-7b-chat", trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained("AIAT/Pangpuriye-openthaigpt-1.0.0-7b-chat", trust_remote_code=True)
+
+schema = """your SQL schema"""
+query = "หาจำนวนลูกค้าที่เป็นเพศชาย"
+
+prompt = f"""
+    [INST] <<SYS>>
+    You are a question answering assistant. Answer the question as truthful and helpful as possible คุณคือผู้ช่วยตอบคำถาม จงตอบคำถามอย่างถูกต้องและมีประโยชน์ที่สุด
+    <</SYS>>
+    {schema}### (sql extract) {query} [/INST]
+"""
+
+tokens = tokenizer(prompt, return_tensors="pt")
+output = model.generate(tokens["input_ids"], max_new_tokens=20, eos_token_id=tokenizer.eos_token_id)
+print(get_prediction(tokenizer.decode(output[0], skip_special_tokens=True)))
+```