Instructions to use SLPL/t5-fa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SLPL/t5-fa with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("SLPL/t5-fa") model = AutoModelForSeq2SeqLM.from_pretrained("SLPL/t5-fa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from SLPL/t5-fa: direct link, hf CLI and curl.
- Browser
- Download file 990 MB
-
https://huggingface.co/SLPL/t5-fa/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://SLPL/t5-fa/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/SLPL/t5-fa/resolve/main/flax_model.msgpack
990 MB
- Xet hash:
- f49a7fc8febc2dfb0b0d2b2dad57ea4b8316b4f58e112e72918fd6bfb5c30ca5
- Size of remote file:
- 990 MB
- SHA256:
- 7892ad18fbaefbb64b0ad9e85806a6c4d74fd3c2a08c1a2d720ae83155047947
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