Summarization
Transformers
PyTorch
JAX
Rust
Safetensors
English
bart
text2text-generation
news
transformer
distilbart
financial-news
encoder-decoder
Instructions to use Sachin21112004/distilbart-news-summarizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sachin21112004/distilbart-news-summarizer 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="Sachin21112004/distilbart-news-summarizer")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Sachin21112004/distilbart-news-summarizer") model = AutoModelForSeq2SeqLM.from_pretrained("Sachin21112004/distilbart-news-summarizer", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from Sachin21112004/distilbart-news-summarizer: direct link, hf CLI and curl.
- Browser
- Download file 1.22 GB
-
https://huggingface.co/Sachin21112004/distilbart-news-summarizer/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://Sachin21112004/distilbart-news-summarizer/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/Sachin21112004/distilbart-news-summarizer/resolve/main/flax_model.msgpack
1.22 GB
- Xet hash:
- dfe860a870fde70de6b9ee478b5b81d7e8180c39d01832398992ee6c53dab05a
- Size of remote file:
- 1.22 GB
- SHA256:
- 2e850d264574dac2076ae01ce78afe398ac02ac4b68e144feb9ca108bb5851c0
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