Translation
Transformers
PyTorch
TensorFlow
JAX
Rust
t5
text-generation
summarization
text-generation-inference
Instructions to use baffo32/t5-base-ptmap with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use baffo32/t5-base-ptmap 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="baffo32/t5-base-ptmap")# Load model directly from transformers import AutoTokenizer, AutoModelWithLMHead tokenizer = AutoTokenizer.from_pretrained("baffo32/t5-base-ptmap") model = AutoModelWithLMHead.from_pretrained("baffo32/t5-base-ptmap") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2f67ba177372f8bc54ad6a65a6ef0f0259df8f616216d8a7c1d1e7117a6b6227
- Size of remote file:
- 892 MB
- SHA256:
- d96ab4b2e2ac1743c32e80669ec37905151c78d8136ff0ce4ba6566bde6e932f
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