Instructions to use versae/t5-4m-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use versae/t5-4m-large with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("versae/t5-4m-large") model = AutoModelForSeq2SeqLM.from_pretrained("versae/t5-4m-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from versae/t5-4m-large: direct link, hf CLI and curl.
- Browser
- Download file 3.13 GB
-
https://huggingface.co/versae/t5-4m-large/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://versae/t5-4m-large/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/versae/t5-4m-large/resolve/main/flax_model.msgpack
3.13 GB
- Xet hash:
- 00164aae1f678dc54b2e4b0127a8f6af29ee558fcb1b94102467dba2896c1072
- Size of remote file:
- 3.13 GB
- SHA256:
- a51e14cb569dd92696a6eb43ebc1ad2a9939e32c52e40add10e393b117fc2f4c
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