Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-small-ff6000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-small-ff6000 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-small-ff6000") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-small-ff6000") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fd6726af43e1247b886d47648b2a51429f1a9bbf62562c48f088ad4951970241
- Size of remote file:
- 443 MB
- SHA256:
- 03055f2989dd524d035a634cc50e5ce012ca2b6e0ee94c8b4f236c351587b8f8
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