Instructions to use echarlaix/t5-small-int8-dynamic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use echarlaix/t5-small-int8-dynamic with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="echarlaix/t5-small-int8-dynamic", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelWithLMHead tokenizer = AutoTokenizer.from_pretrained("echarlaix/t5-small-int8-dynamic") model = AutoModelWithLMHead.from_pretrained("echarlaix/t5-small-int8-dynamic", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Add multilingual to the language tag
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by lbourdois - opened
README.md
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- fr
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- ro
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- de
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tags:
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- int8
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- summarization
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- translation
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---
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## [t5-small](https://huggingface.co/t5-small) exported to the ONNX format and dynamically quantized.
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- fr
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- ro
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- de
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- multilingual
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license: apache-2.0
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tags:
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- int8
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- summarization
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- translation
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datasets:
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- c4
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---
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## [t5-small](https://huggingface.co/t5-small) exported to the ONNX format and dynamically quantized.
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