Instructions to use knkarthick/meeting-summary-samsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use knkarthick/meeting-summary-samsum 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="knkarthick/meeting-summary-samsum")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("knkarthick/meeting-summary-samsum") model = AutoModelForSeq2SeqLM.from_pretrained("knkarthick/meeting-summary-samsum") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ee8aa4102aae67c0c4fc8bc739b38ce282cb7ef7bb2c9d6f18651b3ccc1c3937
- Size of remote file:
- 1.63 GB
- SHA256:
- 8e659ea2d05d70d6e85e2afa0683d4bd3c51c02573d8773db43bbec41a7386df
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