Transformers
PyTorch
JAX
TensorBoard
Safetensors
Yoruba
t5
text2text-generation
text-generation-inference
Instructions to use Davlan/oyo-mt-t5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Davlan/oyo-mt-t5-base with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Davlan/oyo-mt-t5-base") model = AutoModelForSeq2SeqLM.from_pretrained("Davlan/oyo-mt-t5-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from Davlan/oyo-mt-t5-base: direct link, hf CLI and curl.
- Browser
- Download file 1.22 GB
-
https://huggingface.co/Davlan/oyo-mt-t5-base/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://Davlan/oyo-mt-t5-base/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/Davlan/oyo-mt-t5-base/resolve/main/flax_model.msgpack
1.22 GB
- Xet hash:
- 80adb2d38cc2539e8d2e7745d966e47fbb2d8747fe57cdc2cf38b8b928a9f21f
- Size of remote file:
- 1.22 GB
- SHA256:
- 3180dc906ae5a520ab7b1c3b030d4f3156da5d659a736cad1302c6bbddd0f989
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