Model Details
Full Model IDgoogle-t5/t5-small
Pipeline / Tasktranslation
Librarytransformers
Downloads (all-time)24.6M
Likes636
Last Modified6/30/2023
Author / Orggoogle-t5
PrivateNo — public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("translation", model="google-t5/t5-small")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerspytorchtfjaxrustonnxsafetensorst5text2text-generationsummarizationtranslationenfrrodemultilingualdataset:c4arxiv:1805.12471arxiv:1708.00055arxiv:1704.05426arxiv:1606.05250arxiv:1808.09121arxiv:1810.12885arxiv:1905.10044arxiv:1910.09700license:apache-2.0text-generation-inferenceendpoints_compatibledeploy:azureregion:us
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Access model files, inference API, and full documentation on Hugging Face.
Open on Hugging Face →Browse Model Files ↗← Browse All Models🌐 Task: Translation
This model is designed for the Translation task. Explore more models for this use case.
All Translation Models →📊 Popularity
⬇ Downloads24.6M
❤️ Community Likes636
🛠️ Requirements
- →Install: pip install transformers
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.