Zero-Shot Classification
Transformers
Safetensors
GGUF
English
decision-model
system-one
falcondec
lightdec
calibrated-decisions
multiple-choice
intent-classification
customer-support
natural-language-inference
code
guardrails
agents
selective-prediction
falconsai
model-surgeon
attested-lineage
Instructions to use Falconsai/LightDec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Falconsai/LightDec with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="Falconsai/LightDec")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Falconsai/LightDec", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Delete config.json
Browse files- config.json +0 -6
config.json
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{
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"falconsai.synthesized": true,
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"num_hidden_layers": 22,
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"falconsai.tool": "FALCONS.AI Model Surgeon V7.99",
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"falconsai.attn_note": "attention kernel is chosen at load time (e.g. attn_implementation='flash_attention_2' on CUDA/ROCm hosts that have it); nothing in this file selects it"
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}
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