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+
+# Example usage
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import transformers
+import torch
+
+model = "tiiuae/falcon-40B"
+
+tokenizer = AutoTokenizer.from_pretrained(model)
+pipeline = transformers.pipeline(
+    "text-generation",
+    model=model,
+    tokenizer=tokenizer,
+    torch_dtype=torch.bfloat16,
+    trust_remote_code=True,
+    device_map="auto",
+)
+sequences = pipeline(
+    "My favourite data joke is",
+    max_length=200,
+    do_sample=True,
+    top_k=10,
+    num_return_sequences=1,
+    eos_token_id=tokenizer.eos_token_id,
+)
+print("=" * 30)
+print("Results:")
+for seq in sequences:
+    print(f"Result: {seq['generated_text']}")
+
+```