Create README.md

README.md

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+---
+license: apache-2.0
+---
+
+![image/webp](https://cdn-uploads.huggingface.co/production/uploads/6455cc8d679315e4ef16fbec/wZ0eCzTn2CzYB44cmaE6L.webp)
+
+## Code example
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+def generate_response(prompt):
+    """
+    Generate a response from the model based on the input prompt.
+
+    Args:
+    prompt (str): Prompt for the model.
+
+    Returns:
+    str: The generated response from the model.
+    """
+    # Tokenize the input prompt
+    inputs = tokenizer(prompt, return_tensors="pt")
+
+    # Generate output tokens
+    outputs = model.generate(**inputs, max_new_tokens=256, eos_token_id=tokenizer.eos_token_id, pad_token_id=tokenizer.pad_token_id)
+
+    # Decode the generated tokens to a string
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+    return response
+
+# Load the model and tokenizer
+model_id = "macadeliccc/laser-dolphin-mixtral-4x7b-dpo"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id, load_in_4bit=True)
+
+prompt = "Write a quicksort algorithm in python"
+
+# Generate and print responses for each language
+print("Response:")
+print(generate_response(prompt), "\n")
+```