Translation
Transformers
PyTorch
English
Chinese
mbart
text2text-generation
fine tune
fine_tune
mbart-50
Instructions to use Normal1919/mbart-large-50-one-to-many-lil-fine-tune with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Normal1919/mbart-large-50-one-to-many-lil-fine-tune 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="Normal1919/mbart-large-50-one-to-many-lil-fine-tune")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Normal1919/mbart-large-50-one-to-many-lil-fine-tune") model = AutoModelForSeq2SeqLM.from_pretrained("Normal1919/mbart-large-50-one-to-many-lil-fine-tune", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 129d32b5032264fb76805f9d39480c46a7ac431e349a4290b0de275edfa77929
- Size of remote file:
- 2.44 GB
- SHA256:
- 34839d6bf9538ff0e46b40ca4d3ab8d3f5586fc4d680c598785033d54dbf8967
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