Create gpt2_sentence

gpt2_sentence

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+# Use a pipeline as a high-level helper 
+from transformers import pipeline
+
+pipe = pipeline("text-generation", model="gpt2")
+
+# Load model directly
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+tokenizer = AutoTokenizer.from_pretrained("gpt2")
+model = AutoModelForCausalLM.from_pretrained("gpt2")
+
+#get the text
+text_input = "One upon a time there was a tree"
+max_length = 100
+temperature = 0.8
+top_k = 100
+
+input_ids = tokenizer.encode(text_input,return_tensors='pt')
+
+output = model.generate(input_ids, max_length=max_length, temperature=temperature, top_k=top_k, do_sample = True)
+
+
+response = tokenizer.decode(output[0], skip_special_token=True)
+print(response)