Summarization
Transformers
TensorBoard
Safetensors
English
pegasus
text2text-generation
fine-tuned
google-pegasus-xsum
ccdv/govreport-summarization
Instructions to use nppiech/a-text-summarizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nppiech/a-text-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="nppiech/a-text-summarizer")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("nppiech/a-text-summarizer") model = AutoModelForSeq2SeqLM.from_pretrained("nppiech/a-text-summarizer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from nppiech/a-text-summarizer: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/nppiech/a-text-summarizer/resolve/main/training_args.bin
- Command line
-
hf download hf://nppiech/a-text-summarizer/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/nppiech/a-text-summarizer/resolve/main/training_args.bin
5.37 kB
- Xet hash:
- 699fc7733da66b2f7c1cb04dfa360b167f00943f08ac0b1a1703aec6de43254a
- Size of remote file:
- 5.37 kB
- SHA256:
- 990d49fa41395691d1afd535c519ad35c3170418ec0043395da5cc5494001f27
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