Create README.md

README.md

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+## Example
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+import re
+
+model_name = "TabCanNotTab/SALV-Qwen2.5-Coder-7B-Instruct"
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    torch_dtype=torch.bfloat16,
+    device_map="auto",
+)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+prompt = """
+Please act as a professional verilog designer.
+
+Implement a module of an 8-bit adder with multiple bit-level adders in combinational logic. 
+
+Module name:  
+    adder_8bit               
+Input ports:
+    a[7:0]: 8-bit input operand A.
+    b[7:0]: 8-bit input operand B.
+    cin: Carry-in input.
+Output ports:
+    sum[7:0]: 8-bit output representing the sum of A and B.
+    cout: Carry-out output.
+
+Implementation:
+The module utilizes a series of bit-level adders (full adders) to perform the addition operation.
+
+Give me the complete code.
+"""
+
+messages = [
+    {"role": "system", "content": "You are a helpful 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(model.device)
+
+# inference
+outputs = model.generate(
+    **model_inputs,
+    max_new_tokens=2048,
+    do_sample=True,
+    temperature=0.5,
+    top_p=0.95
+)
+
+# get response text
+input_length = model_inputs.input_ids.shape[1]
+generated_tokens = outputs[0][input_length:]
+response = tokenizer.decode(generated_tokens, skip_special_tokens=True)
+
+# get code text
+pattern = r"```verilog\s*(.*?)\s*```"
+matches = re.findall(pattern, response, re.DOTALL)
+if matches:
+    code=matches[-1]
+    print(code)
+else:
+    print("No Verilog code found in the response!")
+```