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
Download manifest.json from Falconsai/proof_v3: direct link, hf CLI and curl.
- Browser
- Download file 2.04 kB
-
https://huggingface.co/Falconsai/proof_v3/resolve/main/manifest.json
- Command line
-
hf download hf://Falconsai/proof_v3/manifest.json
-
curl -L -o manifest.json https://huggingface.co/Falconsai/proof_v3/resolve/main/manifest.json
2.04 kB
| { | |
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| "tool": "FALCONS.AI Model Surgeon V7.99", | |
| "copyright": "\u00a9 2026 FALCONS.AI", | |
| "exported": "2026-09-26T03:18:56Z", | |
| "architecture": { | |
| "family": "transformer_nlp", | |
| "label": "NLP \u00b7 Small Language Model (SLM)", | |
| "confidence": 0.98, | |
| "score": 8.92, | |
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| "tool": "FALCONS.AI Model Surgeon V7.99", | |
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