Summarization
Transformers
TensorBoard
Safetensors
bart
text2text-generation
Generated from Trainer
Eval Results (legacy)
Instructions to use ell11/summary_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ell11/summary_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="ell11/summary_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ell11/summary_model") model = AutoModelForSeq2SeqLM.from_pretrained("ell11/summary_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ell11/summary_model: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/ell11/summary_model/resolve/main/training_args.bin
- Command line
-
hf download hf://ell11/summary_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ell11/summary_model/resolve/main/training_args.bin
4.73 kB
- Xet hash:
- 81e80f5386b8ec878c31e49ffc08950644da48a9138ebab938a52c6df796454e
- Size of remote file:
- 4.73 kB
- SHA256:
- eec0db9fe404c68f89bdb46358fd624f10805cc8fbf6de0fa0a6964aa4071188
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