--- license: apache-2.0 language: - en tags: - ctranslate2 - fastchat-t5-3b - quantization - int8 pipeline_tag: text2text-generation --- # Model Card for FastChat-T5 3B Q8 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. ## Model Details ### Model Description The model being quantized using [CTranslate2](https://opennmt.net/CTranslate2/) with the following command: ``` 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 ``` If you want to perform the quantization yourself, you need to install the following dependencies: ``` pip install -qU ctranslate2 transformers[torch] sentencepiece accelerate ``` - **Shared by:** Lim Chee Kin - **License:** Apache 2.0 ## How to Get Started with the Model Use the code below to get started with the model. ```python import ctranslate2 import transformers translator = ctranslate2.Translator("limcheekin/fastchat-t5-3b-ct2") tokenizer = transformers.AutoTokenizer.from_pretrained("limcheekin/fastchat-t5-3b-ct2") input_text = "translate English to German: The house is wonderful." input_tokens = tokenizer.convert_ids_to_tokens(tokenizer.encode(input_text)) results = translator.translate_batch([input_tokens]) output_tokens = results[0].hypotheses[0] output_text = tokenizer.decode(tokenizer.convert_tokens_to_ids(output_tokens)) print(output_text) ``` The code is taken from https://opennmt.net/CTranslate2/guides/transformers.html#t5. 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).