Summarization
Transformers
TensorBoard
Safetensors
led
text2text-generation
Generated from Trainer
conversatoin_summarizer
Instructions to use StDestiny/DialogLED-base-16384-QMSum-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use StDestiny/DialogLED-base-16384-QMSum-finetuned 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="StDestiny/DialogLED-base-16384-QMSum-finetuned")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("StDestiny/DialogLED-base-16384-QMSum-finetuned") model = AutoModelForSeq2SeqLM.from_pretrained("StDestiny/DialogLED-base-16384-QMSum-finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from StDestiny/DialogLED-base-16384-QMSum-finetuned: direct link, hf CLI and curl.
- Browser
- Download file 5.05 kB
-
https://huggingface.co/StDestiny/DialogLED-base-16384-QMSum-finetuned/resolve/main/training_args.bin
- Command line
-
hf download hf://StDestiny/DialogLED-base-16384-QMSum-finetuned/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/StDestiny/DialogLED-base-16384-QMSum-finetuned/resolve/main/training_args.bin
5.05 kB
- Xet hash:
- 332270b1b650bf1bffee4cec6aacc7be2cfbf6e512a77adc19fa4d6f36c573d3
- Size of remote file:
- 5.05 kB
- SHA256:
- 4d06be3b13e9b036ea266d1d40afe8790c67e89fa8808d33a1993d812c860ab4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.