Instructions to use versae/t5-4m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use versae/t5-4m with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("versae/t5-4m") model = AutoModelForSeq2SeqLM.from_pretrained("versae/t5-4m", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from versae/t5-4m: direct link, hf CLI and curl.
- Browser
- Download file 990 MB
-
https://huggingface.co/versae/t5-4m/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://versae/t5-4m/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/versae/t5-4m/resolve/main/flax_model.msgpack
990 MB
- Xet hash:
- db27b3687dee71bbcb9239dd65161f6adb233b41d895400ee40d2704942fd6b1
- Size of remote file:
- 990 MB
- SHA256:
- c6f401f7237cfac1359d30794250da36aa8f879f6df2db218e059c73c12f3c87
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