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 config.json
Browse files- config.json +2 -1
config.json
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"torch_dtype": "bfloat16",
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"transformers_version": "4.44.0.dev0",
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"use_cache": true,
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"vocab_size": 128256
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}
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"torch_dtype": "bfloat16",
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"transformers_version": "4.44.0.dev0",
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"use_cache": true,
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"vocab_size": 128256,
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"max_new_tokens": 1024
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}
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