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@@ -34,13 +34,28 @@ We use state-of-the-art [Language Model Evaluation Harness](https://github.com/E
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  * **Model type:** **GPT-2-dolly** is an auto-regressive language model based on the GPT-2 transformer architecture.
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  * **Language(s)**: English
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- ### Prompt Template
 
 
 
 
 
 
 
 
 
 
 
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  ```
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- ### Instruction:
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- <prompt> (without the <>)
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- ### Response:
 
 
 
 
 
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  ```
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  ### Training Dataset
 
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  * **Model type:** **GPT-2-dolly** is an auto-regressive language model based on the GPT-2 transformer architecture.
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  * **Language(s)**: English
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+ ### How to use:
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+
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+ ```python
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+ # Use a pipeline as a high-level helper
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+ >>> from transformers import pipeline
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+ >>> pipe = pipeline("text-generation", model="lgaalves/gpt2-dolly")
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+ >>> question = "What is a large language model?"
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+ >>> answer = pipe(question)
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+ >>> print(answer[0]['generated_text'])
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+ What is a large language model?
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+ A large language model aims for understanding a large group of phenomena through computational methods which allow more precise models.
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+ A model also encourages the use of empirical concepts such as equations, models, natural numbers, natural language
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  ```
 
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+ or, you can load the model direclty using:
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+ ```python
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+ # Load model directly
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+ from transformers import AutoTokenizer, AutoModelForCausalLM
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+
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+ tokenizer = AutoTokenizer.from_pretrained("lgaalves/gpt2-dolly")
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+ model = AutoModelForCausalLM.from_pretrained("lgaalves/gpt2-dolly")
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  ```
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  ### Training Dataset