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Delete flan-alpaca-gpt4-xl-ct2

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flan-alpaca-gpt4-xl-ct2/README.md DELETED
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- ---
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- license: apache-2.0
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- language:
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- - en
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- tags:
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- - ctranslate2
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- - flan-alpaca-gpt4-xl
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- - quantization
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- - int8
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- ---
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-
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- # Model Card for Flan-Alpaca-GPT4-XL Q8
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-
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- The model is quantized version of the [declare-lab/flan-alpaca-gpt4-xl](https://huggingface.co/declare-lab/flan-alpaca-gpt4-xl) with int8 quantization.
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-
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- ## Model Details
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-
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- ### Model Description
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-
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- The model being quantized using [CTranslate2](https://opennmt.net/CTranslate2/) with the following command:
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-
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- ```
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- ct2-transformers-converter --model declare-lab/flan-alpaca-gpt4-xl --output_dir declare-lab/flan-alpaca-gpt4-xl-ct2 --copy_files generation_config.json tokenizer.json tokenizer_config.json special_tokens_map.json spiece.model --quantization int8 --force --low_cpu_mem_usage
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- ```
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-
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- If you want to perform the quantization yourself, you need to install the following dependencies:
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-
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- ```
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- pip install -qU ctranslate2 transformers[torch] sentencepiece accelerate
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- ```
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-
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- - **Shared by:** Lim Chee Kin
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- - **License:** Apache 2.0
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-
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- ## How to Get Started with the Model
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-
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- Use the code below to get started with the model.
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-
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- ```python
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- import ctranslate2
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- import transformers
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-
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- translator = ctranslate2.Translator("limcheekin/flan-alpaca-gpt4-xl-ct2")
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- tokenizer = transformers.AutoTokenizer.from_pretrained("limcheekin/flan-alpaca-gpt4-xl-ct2")
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-
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- input_text = "translate English to German: The house is wonderful."
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- input_tokens = tokenizer.convert_ids_to_tokens(tokenizer.encode(input_text))
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-
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- results = translator.translate_batch([input_tokens])
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-
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- output_tokens = results[0].hypotheses[0]
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- output_text = tokenizer.decode(tokenizer.convert_tokens_to_ids(output_tokens))
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-
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- print(output_text)
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- ```
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-
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- The code is taken from https://opennmt.net/CTranslate2/guides/transformers.html#t5.
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-
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- The key method of the code above is `translate_batch`, you can find out [its supported parameters here](https://opennmt.net/CTranslate2/python/ctranslate2.Translator.html#ctranslate2.Translator.translate_batch).
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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