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ternary
/
Arbiter-8B

Text Classification
Transformers
Safetensors
English
qwen3
text-generation
qwen
decision-model
finance
wealth-management
sec-filings
news
calibration
lora
jev
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use ternary/Arbiter-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use ternary/Arbiter-8B with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="ternary/Arbiter-8B")
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForCausalLM
    
    tokenizer = AutoTokenizer.from_pretrained("ternary/Arbiter-8B")
    model = AutoModelForCausalLM.from_pretrained("ternary/Arbiter-8B", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
Arbiter-8B / adapter
349 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
jsemrau's picture
jsemrau
Arbiter v0.4 full model: LoRA merged into the dequantized 4-bit base (fp16), tokenizer, decision head, calibration; adapter kept in adapter/
aa20e73 verified 15 days ago
  • adapter_config.json
    1.27 kB
    Arbiter v0.4: LoRA adapter, decision head, calibration, inference code and model card 15 days ago
  • adapter_model.safetensors
    349 MB
    xet
    Arbiter v0.4: LoRA adapter, decision head, calibration, inference code and model card 15 days ago
  • calibration.json
    461 Bytes
    Arbiter v0.4 full model: LoRA merged into the dequantized 4-bit base (fp16), tokenizer, decision head, calibration; adapter kept in adapter/ 15 days ago