Instructions to use ax13/summarizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ax13/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="ax13/summarizer")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ax13/summarizer") model = AutoModelForSeq2SeqLM.from_pretrained("ax13/summarizer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ax13/summarizer: direct link, hf CLI and curl.
- Browser
- Download file 558 MB
-
https://huggingface.co/ax13/summarizer/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ax13/summarizer/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ax13/summarizer/resolve/main/pytorch_model.bin
558 MB
- Xet hash:
- 6f7cb35c291c53de85595c596e79ced8cf7dfbc3214454861f10510cd5f1935e
- Size of remote file:
- 558 MB
- SHA256:
- ef39df3a558dced6f9df370c7b86d46c31d85604e3c40723c424882b6c71ac44
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