Instructions to use gpssohi/distilbart-qgen-3-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gpssohi/distilbart-qgen-3-3 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="gpssohi/distilbart-qgen-3-3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("gpssohi/distilbart-qgen-3-3") model = AutoModelForSeq2SeqLM.from_pretrained("gpssohi/distilbart-qgen-3-3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from gpssohi/distilbart-qgen-3-3: direct link, hf CLI and curl.
- Browser
- Download file 567 MB
-
https://huggingface.co/gpssohi/distilbart-qgen-3-3/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://gpssohi/distilbart-qgen-3-3/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/gpssohi/distilbart-qgen-3-3/resolve/main/pytorch_model.bin
567 MB
- Xet hash:
- 700b571c0fc9b62efcaa645d364f39d4c73a911c22611b1c5bfc95a3d2180c2e
- Size of remote file:
- 567 MB
- SHA256:
- 106bb425faa6afb3b1cec4a4a8494c4bef7045930847c8de23383b1707f093c1
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