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Update README.md

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Updated README with chat_template

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  1. README.md +28 -20
README.md CHANGED
@@ -38,6 +38,15 @@ DeciLM-7B-instruct is a derivative of the recently released [DeciLM-7B](https://
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  - **Finetuning Notebook:** [DeciLM-7B Finetuning Notebook](https://colab.research.google.com/drive/1kEV6i96AQ94xTCvSd11TxkEaksTb5o3U?usp=sharing)
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  - **Text Generation Notebook:** [DeciLM-7B-instruct Text Generation Notebook](https://bit.ly/declm-7b-instruct)
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  ## Uses
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  The model is intended for commercial and research use in English.
@@ -54,16 +63,21 @@ model_name = "Deci/DeciLM-7B-instruct"
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  device = "cuda" # for GPU usage or "cpu" for CPU usage
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- bnb_config = BitsAndBytesConfig(
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- load_in_4bit = True,
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- bnb_4bit_compute_dtype=torch.bfloat16
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- )
 
 
 
 
 
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  model = AutoModelForCausalLM.from_pretrained(
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  model_name,
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  device_map="auto",
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  trust_remote_code=True,
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- quantization_config=bnb_config
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  )
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  tokenizer = AutoTokenizer.from_pretrained(model_name)
@@ -75,25 +89,19 @@ deci_generator = pipeline("text-generation",
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  temperature=0.1,
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  device_map="auto",
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  max_length=4096,
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- return_full_text=False
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- )
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- prompt = "How do I make the most delicious pancakes the world has ever tasted?"
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- SYSTEM_PROMPT_TEMPLATE ="""
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- ### System:
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- You are an AI assistant that follows instruction extremely well. Help as much as you can.
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- ### User:
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- {instruction}
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- ### Assistant:
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- """
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- # Function to construct the prompt using the new system prompt template
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- def get_prompt_with_template(message: str) -> str:
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- return SYSTEM_PROMPT_TEMPLATE.format(instruction=message)
 
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- response = deci_generator(get_prompt_with_template(prompt))[0]['generated_text']
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- print(response)
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  ```
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  ## Evaluation
 
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  - **Finetuning Notebook:** [DeciLM-7B Finetuning Notebook](https://colab.research.google.com/drive/1kEV6i96AQ94xTCvSd11TxkEaksTb5o3U?usp=sharing)
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  - **Text Generation Notebook:** [DeciLM-7B-instruct Text Generation Notebook](https://bit.ly/declm-7b-instruct)
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+ ### Prompt Template
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+ ```
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+ ### System:
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+ {system_prompt}
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+ ### User:
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+ {user_prompt}
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+ ### Assistant:
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+ ```
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+
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  ## Uses
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  The model is intended for commercial and research use in English.
 
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  device = "cuda" # for GPU usage or "cpu" for CPU usage
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+ quantize = False # Optional. Useful for GPUs with less than 24GB memory
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+
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+ if quantize:
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+ dtype_kwargs = dict(quantization_config=BitsAndBytesConfig(
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+ load_in_4bit=True,
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+ bnb_4bit_compute_dtype=torch.bfloat16
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+ ))
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+ else:
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+ dtype_kwargs = dict(torch_dtype="auto")
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  model = AutoModelForCausalLM.from_pretrained(
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  model_name,
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  device_map="auto",
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  trust_remote_code=True,
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+ **dtype_kwargs
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  )
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  tokenizer = AutoTokenizer.from_pretrained(model_name)
 
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  temperature=0.1,
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  device_map="auto",
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  max_length=4096,
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+ return_full_text=False)
 
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+ system_prompt = "You are an AI assistant that follows instruction extremely well. Help as much as you can."
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+ user_prompt = "How do I make the most delicious pancakes the world has ever tasted?"
 
 
 
 
 
 
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+ prompt = tokenizer.apply_chat_template([
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+ {"role": "system", "content": system_prompt},
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+ {"role": "user", "content": user_prompt},
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+ ], tokenize=False, add_generation_prompt=True)
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+ response = deci_generator(prompt)[0]['generated_text']
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+ print(prompt + response)
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  ```
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  ## Evaluation