README.md · traintogpb/llama-2-enko-translator-7b-qlora-adapter at main

metadata

library_name: peft
base_model: beomi/open-llama-2-ko-7b
license: cc-by-sa-4.0
datasets:
  - traintogpb/aihub-flores-koen-integrated-sparta-30k
language:
  - en
  - ko
metrics:
  - sacrebleu
  - comet
pipeline_tag: translation
tags:
  - translation
  - text-generation
  - ko2en
  - en2ko

Pretrained LM

beomi/open-llama-2-ko-7b (MIT License)

Training Dataset

traintogpb/aihub-flores-koen-integrated-sparta-30k
Can translate in Enlgish-Korean (bi-directional)

Prompt

Template:

  prompt = f"Translate this from {src_lang} to {tgt_lang}\n### {src_lang}: {src_text}\n### {tgt_lang}:"

  >>> # src_lang can be 'English', '한국어'
  >>> # tgt_lang can be '한국어', 'English'

Issue: The tokenizer of the model tokenizes the prompt below in different way with the prompt above. Make sure to use the prompt proposed above.
```
  prompt = f"""Translate this from {src_lang} to {tgt_lang}
  ### {src_lang}: {src_text}
  ### {tgt_lang}:"""

  >>> # DO NOT USE this prompt
```
And mind that there is no "space (_)" at the end of the prompt.

Training

Trained with QLoRA
- PLM: NormalFloat 4-bit
- Adapter: BrainFloat 16-bit
- Adapted to all the linear layers (around 2.2%)

Usage (IMPORTANT)

Should remove the EOS token (<|endoftext|>, id=46332) at the end of the prompt.

  # MODEL
  plm_name = 'beomi/open-llama-2-ko-7b'
  adapter_name = 'traintogpb/llama-2-enko-translator-7b-qlora-adapter'
  model = LlamaForCausalLM.from_pretrained(
      plm_name, 
      max_length=768,
      quantization_config=bnb_config, # Use the QLoRA config above
      attn_implementation='flash_attention_2',
      torch_dtype=torch.bfloat16
  )
  model = PeftModel.from_pretrained(
      model, 
      adapter_name, 
      torch_dtype=torch.bfloat16
  )

  # TOKENIZER
  tokenizer = LlamaTokenizer.from_pretrained(plm_name)
  tokenizer.pad_token = "</s>"
  tokenizer.pad_token_id = 2
  tokenizer.eos_token = "<|endoftext|>" # Must be differentiated from the PAD token
  tokenizer.eos_token_id = 46332
  tokenizer.add_eos_token = True
  tokenizer.model_max_length = 768

  # INFERENCE
  text = "NMIXX is the world-best female idol group, who came back with the new song 'DASH'." 
  prompt = f"Translate this from {src_lang} to {tgt_lang}\n### {src_lang}: {src_text}\n### {tgt_lang}:"

  inputs = tokenizer(prompt, return_tensors="pt", max_length=max_length, truncation=True)
  # REMOVE EOS TOKEN IN THE PROMPT
  inputs['input_ids'] = inputs['input_ids'][0][:-1].unsqueeze(dim=0)
  inputs['attention_mask'] = inputs['attention_mask'][0][:-1].unsqueeze(dim=0)

  outputs = model.generate(**inputs, max_length=max_length, eos_token_id=46332)

  input_len = len(inputs['input_ids'].squeeze())
          
  translated_text = tokenizer.decode(outputs[0][input_len:], skip_special_tokens=True)
  print(translated_text)