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:
- e10c5be3890d99e65a2fc5643a3133e091f453226705dfb90a59743480893567
- Size of remote file:
- 1,000 MB
- SHA256:
- e9c1f1d1fb3d8a3653d7a35662c6ec0a3a8f72c9191f71dd1c77b89c35c64170
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