Transformers
PyTorch
Safetensors
Polish
t5
text2text-generation
T5
lemmatization
text-generation-inference
Instructions to use amu-cai/polemma-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amu-cai/polemma-base with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("amu-cai/polemma-base") model = AutoModelForSeq2SeqLM.from_pretrained("amu-cai/polemma-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0189884c43cfc3cde9d6c790ae901d9db298e55ec46a10cc37cb54097030cf8f
- Size of remote file:
- 1.12 MB
- SHA256:
- a200b4b9d7106b32ea2340e5cd27033a5c03ae5ece9241ab6e1f685b938800b9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.