Create README.md

README.md

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+from datasets import load_dataset
+
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+dataset = load_dataset("CarperAI/openai_summarize_tldr")
+
+val_prompts = [sample["prompt"] for sample in dataset["valid"]]
+
+kwargs = {
+    "max_new_tokens": 50,
+    "do_sample": True,
+    "top_k": 0,
+    "top_p": 0.95,
+    "temperature": 0.5
+}
+
+model = AutoModelForCausalLM.from_pretrained("pvduy/ppo_pythia6B_sample")
+model.eval()
+tokenizer = AutoTokenizer.from_pretrained("pvduy/ppo_pythia6B_sample")
+tokenizer.pad_token_id = tokenizer.eos_token_id
+
+count = 0
+
+for prompt in val_prompts:
+    output_tk = tokenizer(prompt, return_tensors="pt")
+    outputs = model.generate(output_tk.input_ids, attention_mask=output_tk.attention_mask, **kwargs)
+    print("Prompt:", prompt)
+    print("Output:", tokenizer.decode(outputs[0], skip_special_tokens=True).split("TL;DR:")[1].strip())
+    print("=================================")
+    count += 1
+    if count == 10:
+        break