Create README.md

README.md

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+---
+library_name: transformers
+license: apache-2.0
+datasets:
+- Porameht/customer-support-th-26.9k
+language:
+- th
+---
+
+## How to use
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+# Ensure CUDA is available
+device = 'cuda' if torch.cuda.is_available() else 'cpu'
+print(f"Using device: {device}")
+# Init Model
+model_path="Porameht/openthaigpt-7b-customer-support-th"
+tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained(model_path, trust_remote_code=True, torch_dtype=torch.float16)
+model.to(device)
+# Prompt
+prompt = "ต้องการยกเลิกออเดอร์"
+llama_prompt = f"<s>[INST] <<SYS>>\nYou are a question answering assistant. Answer the question as truthful and helpful as possible คุณคือผู้ช่วยตอบคำถาม จงตอบคำถามอย่างถูกต้องและมีประโยชน์ที่สุด<</SYS>>\n\n{prompt} [/INST]"
+inputs = tokenizer.encode(llama_prompt, return_tensors="pt")
+inputs = inputs.to(device)
+# Generate
+outputs = model.generate(inputs, max_length=512, num_return_sequences=1)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```