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minuva
/
MiniLMv2-agentflow-v2-onnx

Text Classification
Transformers
ONNX
English
roberta
int8
optimum
ONNXRuntime
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use minuva/MiniLMv2-agentflow-v2-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use minuva/MiniLMv2-agentflow-v2-onnx with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="minuva/MiniLMv2-agentflow-v2-onnx")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("minuva/MiniLMv2-agentflow-v2-onnx")
    model = AutoModelForSequenceClassification.from_pretrained("minuva/MiniLMv2-agentflow-v2-onnx")
  • Notebooks
  • Google Colab
  • Kaggle
MiniLMv2-agentflow-v2-onnx
33.8 MB
Ctrl+K
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  • 2 contributors
History: 17 commits
Ngit's picture
Ngit
add ONNXRuntime tag
44b771f verified about 2 years ago
  • .gitattributes
    1.52 kB
    initial commit over 2 years ago
  • README.md
    6.18 kB
    add ONNXRuntime tag about 2 years ago
  • config.json
    1.42 kB
    update model over 2 years ago
  • merges.txt
    456 kB
    Upload 8 files over 2 years ago
  • model_optimized_quantized.onnx
    30.5 MB
    xet
    update model over 2 years ago
  • ort_config.json
    830 Bytes
    Upload 8 files over 2 years ago
  • special_tokens_map.json
    958 Bytes
    Upload 8 files over 2 years ago
  • tokenizer.json
    2.11 MB
    Upload 8 files over 2 years ago
  • tokenizer_config.json
    1.32 kB
    Upload 8 files over 2 years ago
  • vocab.json
    798 kB
    Upload 8 files over 2 years ago