Zero-Shot Classification
Transformers
GGUF
English
decision-model
system-one
falcondec
calibrated-decisions
multiple-choice
intent-classification
customer-support
natural-language-inference
code
guardrails
selective-prediction
falconsai
model-surgeon
attested-lineage
Instructions to use Falconsai/proof_v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Falconsai/proof_v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="Falconsai/proof_v3")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Falconsai/proof_v3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
23 days ago
-
Upload 9 files
Verified signature6bf0bc1 -
Update README.md
Verified signature04e1611 -
Upload falconsai_surgeon_package_20260926-031857.zip with huggingface_hub
Verified signaturefbb7a25 -
Upload model_edited.F16.gguf with huggingface_hub
Verified signaturee809c3c -
Upload surgery_log.json with huggingface_hub
Verified signature4df33ae -
Upload manifest.json with huggingface_hub
Verified signature99d3cb5 -
Upload lineage.intoto.jsonl with huggingface_hub
Verified signatured5037a8 -
Upload README.md with huggingface_hub
Verified signature8e2712c -
Upload config.json with huggingface_hub
Verified signaturea31abf3 -
Upload model_edited.safetensors with huggingface_hub
Verified signaturee52733d -
initial commit
Verified signaturecc85c97