Instructions to use diana9m/t5_kd4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use diana9m/t5_kd4 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="diana9m/t5_kd4")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("diana9m/t5_kd4") model = AutoModelForSeq2SeqLM.from_pretrained("diana9m/t5_kd4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3840544eb13c1f6b57c44957ed02cbe5567343665462105378b92e2df4a41bd4
- Size of remote file:
- 1.2 GB
- SHA256:
- 26e2bb73208753a0f235c7105cf62b6e803fd9c3d7ee7e955b8aa4c19b6dcc26
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