Instructions to use versae/t5-10m-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use versae/t5-10m-large with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("versae/t5-10m-large") model = AutoModelForSeq2SeqLM.from_pretrained("versae/t5-10m-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from versae/t5-10m-large: direct link, hf CLI and curl.
- Browser
- Download file 3.13 GB
-
https://huggingface.co/versae/t5-10m-large/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://versae/t5-10m-large/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/versae/t5-10m-large/resolve/main/flax_model.msgpack
3.13 GB
- Xet hash:
- 129db0d46d508caa09d6385f94de63196247d0ccc14b6876665d3206a6abd5b0
- Size of remote file:
- 3.13 GB
- SHA256:
- 2ee786c1a44cc40915c540a62a5b5f3104e3554ad2552269774fbbfc255324c4
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