Summarization
Transformers
PyTorch
English
t5
text2text-generation
Trained with AutoTrain
text-generation-inference
Instructions to use AryaParikh/summ_arp_org with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AryaParikh/summ_arp_org 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="AryaParikh/summ_arp_org")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("AryaParikh/summ_arp_org") model = AutoModelForSeq2SeqLM.from_pretrained("AryaParikh/summ_arp_org", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from AryaParikh/summ_arp_org: direct link, hf CLI and curl.
- Browser
- Download file 2.95 GB
-
https://huggingface.co/AryaParikh/summ_arp_org/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://AryaParikh/summ_arp_org/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/AryaParikh/summ_arp_org/resolve/main/pytorch_model.bin
2.95 GB
- Xet hash:
- 818f4d3c9f7f756cadc9dca8957e539eff089ccce1a9ef427be130ad1684285b
- Size of remote file:
- 2.95 GB
- SHA256:
- 018c32d36e753bf34d1b8a40adb64669d98c8a2589aefd44c8263f2cea675029
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