Create README.md

README.md

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+# This model can generate the solution to problem in [LeetCode](https://leetcode.com)
+
+## The training data: [codellama/CodeLlama-7b-Instruct-hf](https://huggingface.co/datasets/khaimaitien/leetcode_problem_solution)
+## The base model: [codellama/CodeLlama-7b-Instruct-hf](https://huggingface.co/codellama/CodeLlama-7b-Instruct-hf)
+You can find more information at: https://github.com/khaimt/coding_challenge_solver
+
+The prompt template is:
+``` python
+prompt_str = (
+            f"[INST] Write code to solve the following coding problem that obeys"
+            f"the constraints and passes the example test cases."
+            f"Please wrap your code answer using ```:\n{input}\n[/INST]```python\n"
+        )
+```
+Where input is the problem in LeetCode, an example is: https://github.com/khaimt/coding_challenge_solver/blob/main/test_cases/problem1.txt
+
+**Example for inference:**
+
+```python
+prompt_str = (
+            f"[INST] Write code to solve the following coding problem that obeys"
+            f"the constraints and passes the example test cases."
+            f"Please wrap your code answer using ```:\n{input}\n[/INST]```python\n"
+        )
+model = AutoModelForCausalLM.from_pretrained(model_path, device_map="auto", torch_dtype=torch.bfloat16)
+token_ids = tokenizer([prompt_str], return_tensors="pt")["input_ids"]
+token_ids = token_ids.to(model.device)
+outputs = model.generate(input_ids=token_ids, max_new_tokens=1024, do_sample=True, temperature=0.0001)
+all_token_ids = outputs[0].tolist()
+ouput_token_ids = all_token_ids[token_ids.shape[-1] :]
+output = tokenizer.decode(ouput_token_ids)
+print("-------------Solution generated from Model---------")
+print(output)
+```