Summarization
Transformers
PyTorch
Safetensors
bart
text2text-generation
distilbart
Eval Results (legacy)
Instructions to use DeepNLP-22-23/MLQ-distilbart-bbc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DeepNLP-22-23/MLQ-distilbart-bbc 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="DeepNLP-22-23/MLQ-distilbart-bbc")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("DeepNLP-22-23/MLQ-distilbart-bbc") model = AutoModelForSeq2SeqLM.from_pretrained("DeepNLP-22-23/MLQ-distilbart-bbc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Librarian Bot: Add base_model information to model (#2)
- Librarian Bot: Add base_model information to model (85baeb808612530f401c378e4962befa79e89e64) Co-authored-by: Librarian Bot (Bot) <librarian-bot@users.noreply.huggingface.co>a28ddd5
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (596fc2fffbe923d9c9179f125029a316c0ab9d91) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>03e3513
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Create README.md
a9f45b9 -
Upload BartForConditionalGeneration
b80bbba -
Upload tokenizer
6fa0bff -
initial commit
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