# LoRA + llama-2-chat + Tesla T4 15 mins = Emoji ChatBot

## Try yourself

### Expected answers

```
What can I surprise my wife?🎁💕

What can I surprise my kids?🎉👧�

What can I surprise my parents?🎁👪

What can I surprise my friends?🎉🤝
```

### Code to reproduce
```python
# !pip install -q bitsandbytes
# !pip install -q peft
# !pip install -q transformers
# !pip install sentencepiece

from peft import PeftModel
import transformers
import torch
from transformers import LlamaTokenizer, LlamaForCausalLM

model_name_or_path = "daryl149/llama-2-7b-chat-hf"
tokenizer_name_or_path = "daryl149/llama-2-7b-chat-hf"

tokenizer = LlamaTokenizer.from_pretrained(tokenizer_name_or_path)
tokenizer.pad_token_id = 0
tokenizer.padding_side = "left"

original_8bit_llama_model = LlamaForCausalLM.from_pretrained(
    model_name_or_path,
    device_map="auto",
    load_in_8bit=True)


emoji_model = PeftModel.from_pretrained(
    original_8bit_llama_model, "hululuzhu/llama2-chat-emoji-lora")

CUTOFF_LEN = 48
def tokenize(tokenizer, prompt, cutoff_len, add_eos_token=True):
  result = tokenizer(
      prompt,
      truncation=True,
      max_length=cutoff_len,
      padding=False,
      return_tensors=None,
  )
  if (
      result["input_ids"][-1] != tokenizer.eos_token_id
      and len(result["input_ids"]) < cutoff_len
      and add_eos_token
  ):
    result["input_ids"].append(tokenizer.eos_token_id)
    result["attention_mask"].append(1)
  result["labels"] = result["input_ids"].copy()
  return result

def answer(p_in, my_model=emoji_model):
  batch = tokenizer(
      p_in,
      return_tensors='pt',
  )
  with torch.cuda.amp.autocast(): # required for mixed precisions
    output_tokens = my_model.generate(
        **batch, max_new_tokens=batch['input_ids'].shape[-1])
  # print(output_tokens[0])
  out = tokenizer.decode(output_tokens[0], skip_special_tokens=True)
  # My own post-processing logic to "cheat" to align chars
  if len(out) > len(p_in) * 2 - 7:
    out = out[:len(p_in) * 2 - 7 - len(out)] # perfectly match chars
  # replace the last N for visibility
  if out.count('\n') > 1:
    out = out[::-1].replace("\n", "n\\", 1)[::-1]
  # if out.startswith(p_in):
  #   out = out[len(p_in):]
  print(out)
  print()

answer("What can I surprise my wife?")
answer("What can I surprise my kids?")
answer("What can I surprise my parents?")
answer("What can I surprise my friends?")
```