Example of response generation with optional arguments (#853)

* Generate response with optional arguments

* Reference response generation example

* Include transformers and sentencepiece

* Update example to run Mistral-7B-Instruct-v0.3

* Link to generation example

* Style changes from pre-commit

llms/mlx_lm/examples/generate_response.py

@@ -0,0 +1,40 @@
+from mlx_lm import generate, load
+
+# Specify the checkpoint
+checkpoint = "mistralai/Mistral-7B-Instruct-v0.3"
+
+# Load the corresponding model and tokenizer
+model, tokenizer = load(path_or_hf_repo=checkpoint)
+
+# Specify the prompt and conversation history
+prompt = "Why is the sky blue?"
+conversation = [{"role": "user", "content": prompt}]
+
+# Transform the prompt into the chat template
+prompt = tokenizer.apply_chat_template(
+    conversation=conversation, tokenize=False, add_generation_prompt=True
+)
+
+# Specify the maximum number of tokens
+max_tokens = 1_000
+
+# Specify if tokens and timing information will be printed
+verbose = True
+
+# Some optional arguments for causal language model generation
+generation_args = {
+    "temp": 0.7,
+    "repetition_penalty": 1.2,
+    "repetition_context_size": 20,
+    "top_p": 0.95,
+}
+
+# Generate a response with the specified settings
+response = generate(
+    model=model,
+    tokenizer=tokenizer,
+    prompt=prompt,
+    max_tokens=max_tokens,
+    verbose=verbose,
+    **generation_args,
+)