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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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- fastchat-t5-3b |
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- quantization |
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- int8 |
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pipeline_tag: text2text-generation |
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--- |
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# Model Card for FastChat-T5 3B Q8 |
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The model is quantized version of the [lmsys/fastchat-t5-3b-v1.0](https://huggingface.co/lmsys/fastchat-t5-3b-v1.0) with int8 quantization. |
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## Model Details |
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### Model Description |
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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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ct2-transformers-converter --model lmsys/fastchat-t5-3b --output_dir lmsys/fastchat-t5-3b-ct2 --copy_files generation_config.json added_tokens.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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If you want to perform the quantization yourself, you need to install the following dependencies: |
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``` |
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pip install -qU ctranslate2 transformers[torch] sentencepiece accelerate |
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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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## How to Get Started with the Model |
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Use the code below to get started with the model. |
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```python |
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import ctranslate2 |
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import transformers |
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translator = ctranslate2.Translator("limcheekin/fastchat-t5-3b-ct2") |
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tokenizer = transformers.AutoTokenizer.from_pretrained("limcheekin/fastchat-t5-3b-ct2") |
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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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results = translator.translate_batch([input_tokens]) |
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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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print(output_text) |
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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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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). |