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README.md

@@ -35,4 +35,25 @@ This is an attempt to replicate the RLHF pipeline
 ### Reinforcement Learning
 
   For RL we used the code of [trlx](https://github.com/CarperAI/trlx) and prompts from
-  - [fnlp/moss-002-sft-data](https://huggingface.co/datasets/fnlp/moss-002-sft-data/tree/main)
+  - [fnlp/moss-002-sft-data](https://huggingface.co/datasets/fnlp/moss-002-sft-data/tree/main)
+
+### Example
+
+  We used Vicuna v1.1 template for model training
+
+  ```
+  from transformers import AutoModelForCausalLM, AutoTokenizer
+
+  checkpoint = "keyfan/bloomz-rlhf"
+
+  tokenizer = AutoTokenizer.from_pretrained(checkpoint)
+  model = AutoModelForCausalLM.from_pretrained(checkpoint).cuda()
+
+  template = ("A chat between a curious human and an artificial intelligence assistant. "
+              "The assistant gives helpful, detailed, and polite answers to the human's questions. "
+              "USER: {}\nASSISTANT:")
+  question = template.format("Who was the president of the United States in 1955?")
+  inputs = tokenizer.encode(question, return_tensors="pt").cuda()
+  outputs = model.generate(inputs, do_sample=True, top_p=0.8, max_new_tokens=512)
+  print(tokenizer.decode(outputs[0]))
+  ```

pytorch_model-00001-of-00002.bin

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pytorch_model-00002-of-00002.bin

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