Instructions to use DISLab/SummLlama3.2-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DISLab/SummLlama3.2-3B 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="DISLab/SummLlama3.2-3B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("DISLab/SummLlama3.2-3B") model = AutoModelForCausalLM.from_pretrained("DISLab/SummLlama3.2-3B") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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**SummLlama3-70B**,
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https://huggingface.co/DISLab/SummLlama3-70B
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**SummLlama3.1-Series**
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**SummLlama3-70B**,
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https://huggingface.co/DISLab/SummLlama3-8B
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https://huggingface.co/DISLab/SummLlama3-70B
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**SummLlama3.1-Series**
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