Instructions to use maan909/unisumm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use maan909/unisumm 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="maan909/unisumm")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("maan909/unisumm") model = AutoModelForSeq2SeqLM.from_pretrained("maan909/unisumm") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dfe860a870fde70de6b9ee478b5b81d7e8180c39d01832398992ee6c53dab05a
- Size of remote file:
- 1.22 GB
- SHA256:
- 2e850d264574dac2076ae01ce78afe398ac02ac4b68e144feb9ca108bb5851c0
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