Summarization
Transformers
TensorBoard
Safetensors
English
t5
text2text-generation
summarizer
text summarization
abstractive summarization
text-generation-inference
Instructions to use KipperDev/t5_summarizer_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KipperDev/t5_summarizer_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="KipperDev/t5_summarizer_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("KipperDev/t5_summarizer_model") model = AutoModelForSeq2SeqLM.from_pretrained("KipperDev/t5_summarizer_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from KipperDev/t5_summarizer_model: direct link, hf CLI and curl.
- Browser
- Download file 242 MB
-
https://huggingface.co/KipperDev/t5_summarizer_model/resolve/main/model.safetensors
- Command line
-
hf download hf://KipperDev/t5_summarizer_model/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/KipperDev/t5_summarizer_model/resolve/main/model.safetensors
242 MB
- Xet hash:
- 93f3d489d037b17cd604850b387715ee68bd6355aa65185c62cbc3b58973a0d6
- Size of remote file:
- 242 MB
- SHA256:
- 605f630eb2cee6d822220f2ac90d85081fb650fdde92d23ce1aca216483f39da
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