Translation
Transformers
PyTorch
JAX
TensorBoard
Dutch
English
t5
text2text-generation
seq2seq
text-generation-inference
Instructions to use yhavinga/t5-small-24L-ccmatrix-multi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yhavinga/t5-small-24L-ccmatrix-multi with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="yhavinga/t5-small-24L-ccmatrix-multi")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("yhavinga/t5-small-24L-ccmatrix-multi") model = AutoModelForSeq2SeqLM.from_pretrained("yhavinga/t5-small-24L-ccmatrix-multi") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9a911263dd91b99b1e81f851f16c37eb7d8a080fb8ff8da169a3808dd6c63588
- Size of remote file:
- 1 GB
- SHA256:
- 7fa179b29ac7ae828f5ba4c402f4f96c45dc0937ee5f0039e921a2bd2c471ea0
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