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yasserrmd
/
enterprise-reflex-v1

Text Classification
Transformers
Safetensors
English
modernbert
enterprise-ai
agentic-ai
system-1
system-2
action-ranking
action-selection
tool-selection
dynamic-actions
selective-prediction
abstention
no-action
enterprise-agents
workflow-routing
decision-model
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use yasserrmd/enterprise-reflex-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use yasserrmd/enterprise-reflex-v1 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="yasserrmd/enterprise-reflex-v1")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("yasserrmd/enterprise-reflex-v1")
    model = AutoModelForSequenceClassification.from_pretrained("yasserrmd/enterprise-reflex-v1", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
enterprise-reflex-v1
602 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 5 commits
yasserrmd's picture
yasserrmd
Update README.md
80dffdd verified 6 days ago
  • .gitattributes
    1.52 kB
    initial commit 7 days ago
  • README.md
    17.5 kB
    Update README.md 6 days ago
  • config.json
    1.99 kB
    Upload ModernBertForSequenceClassification 7 days ago
  • enterprise_reflex_config.json
    373 Bytes
    Upload enterprise_reflex_config.json with huggingface_hub 7 days ago
  • model.safetensors
    598 MB
    xet
    Upload ModernBertForSequenceClassification 7 days ago
  • tokenizer.json
    3.58 MB
    Upload tokenizer 7 days ago
  • tokenizer_config.json
    380 Bytes
    Upload tokenizer 7 days ago