Instructions to use versae/t5-5m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use versae/t5-5m with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("versae/t5-5m") model = AutoModelForSeq2SeqLM.from_pretrained("versae/t5-5m", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from versae/t5-5m: direct link, hf CLI and curl.
- Browser
- Download file 990 MB
-
https://huggingface.co/versae/t5-5m/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://versae/t5-5m/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/versae/t5-5m/resolve/main/flax_model.msgpack
990 MB
- Xet hash:
- 07c626b3d1c66c6138dc81661195155d590c071f4d133f0bd94b48c0a39e57b7
- Size of remote file:
- 990 MB
- SHA256:
- 61452b20313ed09cd7eb870d61e14516bbad5f2b28ccd76cfe095bb22488ef62
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.