Instructions to use Turkish-NLP/t5-efficient-large-turkish with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Turkish-NLP/t5-efficient-large-turkish with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Turkish-NLP/t5-efficient-large-turkish") model = AutoModelForSeq2SeqLM.from_pretrained("Turkish-NLP/t5-efficient-large-turkish", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Turkish-NLP/t5-efficient-large-turkish: direct link, hf CLI and curl.
- Browser
- Download file 4.36 GB
-
https://huggingface.co/Turkish-NLP/t5-efficient-large-turkish/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Turkish-NLP/t5-efficient-large-turkish/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Turkish-NLP/t5-efficient-large-turkish/resolve/main/pytorch_model.bin
4.36 GB
- Xet hash:
- 05d5725af3344029f0763c1cae862a4c0111e7aed337dc2684c0ac658e5fb320
- Size of remote file:
- 4.36 GB
- SHA256:
- 7a9bf2a75ed52ec68cc8bb59de248f6e9b5681b290d2363d950d98f3facc2a01
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.