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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 424b313078da7e21905be37ebe9dbe8bf7efe5099b7290676ea2f8b09f9b8ac3
- Size of remote file:
- 558 MB
- SHA256:
- 256b3a445f8a84be0ec21c6ea904deea8545c97aab39772aea101fd64cae89aa
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