Summarization
Transformers
PyTorch
Safetensors
bart
text2text-generation
Generated from Trainer
hindi
seq2seq
Instructions to use Someman/bart-hindi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Someman/bart-hindi 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="Someman/bart-hindi")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Someman/bart-hindi") model = AutoModelForSeq2SeqLM.from_pretrained("Someman/bart-hindi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6ed111eecc5f6aed9c24cfe3fcecb99318200b73038e53278042f8fb772978d0
- Size of remote file:
- 3.96 kB
- SHA256:
- c05d5d6207d8c0e00178ba06b335489ae3c389351b748277bedf1c4645105737
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