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
File size: 256 Bytes
3ba9856 | 1 2 3 4 5 6 7 8 9 10 11 12 13 | {
"_from_model_config": true,
"bos_token_id": 0,
"decoder_start_token_id": 2,
"early_stopping": true,
"eos_token_id": 2,
"forced_eos_token_id": 2,
"max_length": 200,
"num_beams": 5,
"pad_token_id": 1,
"transformers_version": "4.31.0"
}
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