Summarization
Transformers
PyTorch
t5
text2text-generation
Generated from Trainer
Eval Results (legacy)
text-generation-inference
Instructions to use Andyrasika/summarization_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Andyrasika/summarization_model 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="Andyrasika/summarization_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Andyrasika/summarization_model") model = AutoModelForSeq2SeqLM.from_pretrained("Andyrasika/summarization_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Andyrasika/summarization_model: direct link, hf CLI and curl.
- Browser
- Download file 242 MB
-
https://huggingface.co/Andyrasika/summarization_model/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://Andyrasika/summarization_model@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Andyrasika/summarization_model/resolve/refs%2Fpr%2F1/pytorch_model.bin
242 MB
- Xet hash:
- 94f9b818e9c6c278d289bf462931cfb10412285b631d88463f0bbef1ebcd8c52
- Size of remote file:
- 242 MB
- SHA256:
- 9dc1b7929b4e3646c5d831f361971cba34f3e1cf5c32af74697db7d66c1ef3d5
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