Summarization
Transformers
PyTorch
TensorFlow
Safetensors
English
bart
text2text-generation
seq2seq
Eval Results (legacy)
Instructions to use knkarthick/MEETING_SUMMARY with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use knkarthick/MEETING_SUMMARY 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")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("knkarthick/MEETING_SUMMARY") model = AutoModelForSeq2SeqLM.from_pretrained("knkarthick/MEETING_SUMMARY", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 065fdb6597a4afb793e1f1703652bee9f2cdfb7d400ee066ab8e9c89771a3d0e
- Size of remote file:
- 1.63 GB
- SHA256:
- 37a02df52d1a613a7cdbdccce4a0278fa6ba846cfd3937d33f69c42c2b9ec25a
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