Translation
Transformers
PyTorch
JAX
TensorBoard
Dutch
English
t5
text2text-generation
seq2seq
text-generation-inference
Instructions to use yhavinga/t5-base-36L-ccmatrix-multi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yhavinga/t5-base-36L-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-base-36L-ccmatrix-multi")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("yhavinga/t5-base-36L-ccmatrix-multi") model = AutoModelForSeq2SeqLM.from_pretrained("yhavinga/t5-base-36L-ccmatrix-multi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from yhavinga/t5-base-36L-ccmatrix-multi: direct link, hf CLI and curl.
- Browser
- Download file 2.92 GB
-
https://huggingface.co/yhavinga/t5-base-36L-ccmatrix-multi/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://yhavinga/t5-base-36L-ccmatrix-multi/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/yhavinga/t5-base-36L-ccmatrix-multi/resolve/main/flax_model.msgpack
2.92 GB
- Xet hash:
- 05886abd45f9983120a559fa10e6e56c4ebb37419c5039da4fd2047ff2daead5
- Size of remote file:
- 2.92 GB
- SHA256:
- 8da2e730c185a9be10da9a9c61c4219c53264938edf050da795c47644f333e4d
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