Instructions to use DISLab/SummLlama3.1-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DISLab/SummLlama3.1-8B 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/SummLlama3.1-8B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("DISLab/SummLlama3.1-8B") model = AutoModelForCausalLM.from_pretrained("DISLab/SummLlama3.1-8B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 189 Bytes
7c93808 | 1 2 3 4 5 6 7 8 9 10 11 12 13 | {
"bos_token_id": 128000,
"do_sample": true,
"eos_token_id": [
128001,
128008,
128009
],
"temperature": 0.6,
"top_p": 0.9,
"transformers_version": "4.44.0.dev0"
}
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