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procedure2012
/
Pulsar-Knowledge-RAG

Feature Extraction
Transformers
PyTorch
bert
Model card Files Files and versions
xet
Community

Instructions to use procedure2012/Pulsar-Knowledge-RAG with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use procedure2012/Pulsar-Knowledge-RAG with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="procedure2012/Pulsar-Knowledge-RAG")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("procedure2012/Pulsar-Knowledge-RAG")
    model = AutoModel.from_pretrained("procedure2012/Pulsar-Knowledge-RAG", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
Pulsar-Knowledge-RAG
4.54 kB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 4 commits
procedure2012's picture
procedure2012
Update README with evaluation results for all 15 benchmarks
a1ecac3 verified about 8 hours ago
  • figures
    Add figures for README about 8 hours ago
  • .gitattributes
    1.52 kB
    initial commit about 8 hours ago
  • README.md
    2.55 kB
    Update README with evaluation results for all 15 benchmarks about 8 hours ago
  • config.json
    69 Bytes
    Upload Pulsar-Knowledge-RAG model (step_1760 - best eval_accuracy: 0.751) about 8 hours ago
  • pytorch_model.bin

    Pickle imports

    • No problematic imports detected

    What is a pickle import?

    23 Bytes
    xet
    Upload Pulsar-Knowledge-RAG model (step_1760 - best eval_accuracy: 0.751) about 8 hours ago