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ZaandaTeika
/
Qwen2.5-Math-1.5B-SHARP-Step

Text Classification
Transformers
Safetensors
English
qwen2
feature-extraction
prm
process-reward-model
reward model
math
hallucination-detection
custom_code
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use ZaandaTeika/Qwen2.5-Math-1.5B-SHARP-Step with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use ZaandaTeika/Qwen2.5-Math-1.5B-SHARP-Step with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="ZaandaTeika/Qwen2.5-Math-1.5B-SHARP-Step", trust_remote_code=True)
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("ZaandaTeika/Qwen2.5-Math-1.5B-SHARP-Step", trust_remote_code=True)
    model = AutoModel.from_pretrained("ZaandaTeika/Qwen2.5-Math-1.5B-SHARP-Step", trust_remote_code=True, device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
Qwen2.5-Math-1.5B-SHARP-Step
3.11 GB
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  • 1 contributor
History: 3 commits
ZaandaTeika's picture
ZaandaTeika
Update README.md
0a13e27 verified about 1 month ago
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