Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-small-kv128 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-small-kv128 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-small-kv128") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-small-kv128") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1ce5761c21b61f18b32ffd22c64ed8b5c9b89b40565f94dabfc80f6deef231d7
- Size of remote file:
- 318 MB
- SHA256:
- 126aee8082fb96ef656d91b05f29221ab4eac9b7b91ba409d9b9505435682137
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