Add beam deployment example

examples/beam-cloud/README.md

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+## Deploy Outlines on Beam
+
+1. Create an account [here](https://beam.cloud) and install the Beam SDK
+2. Download the `app.py` file to your computer
+3. Deploy it as a serverless API by running: `beam deploy app.py:predict`

examples/beam-cloud/app.py

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+from beam import Image, endpoint, env
+
+if env.is_remote():
+    import outlines
+
+
+# Pre-load models when the container first starts
+def load_models():
+    import outlines
+
+    model = outlines.models.transformers("microsoft/Phi-3-mini-4k-instruct")
+    return model
+
+
+@endpoint(
+    name="outlines-serverless",
+    gpu="A10G",
+    cpu=1,
+    memory="16Gi",
+    on_start=load_models,
+    image=Image().add_python_packages(
+        ["outlines", "torch", "transformers", "accelerate"]
+    ),
+)
+def predict(context, **inputs):
+    default_prompt = """You are a sentiment-labelling assistant.
+    Is the following review positive or negative?
+
+    Review: This restaurant is just awesome!
+    """
+
+    prompt = inputs.get("prompt", default_prompt)
+
+    # Unpack cached model from context
+    model = context.on_start_value
+    # Inference
+    generator = outlines.generate.choice(model, ["Positive", "Negative"])
+    answer = generator(prompt)
+    return {"answer": answer}