Summarization
Transformers
PyTorch
TensorBoard
mbart
text2text-generation
fa
Abstractive Summarization
Generated from Trainer
Instructions to use eslamxm/mbart-finetuned-fa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eslamxm/mbart-finetuned-fa with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" 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("summarization", model="eslamxm/mbart-finetuned-fa")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("eslamxm/mbart-finetuned-fa") model = AutoModelForSeq2SeqLM.from_pretrained("eslamxm/mbart-finetuned-fa") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 70f13de80f16326e6eae6096adf133ae26f956b12335aa34b2522b9d22fffbe4
- Size of remote file:
- 2.44 GB
- SHA256:
- 1cbf54a0244a72769e425f410129415597e879ee764956798313c73a968476a9
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