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Falconsai
/
proof_v2

Text Classification
Transformers
Safetensors
GGUF
English
modernbert
feature-extraction
falconsproof
intfalcon
decision-model
zero-shot-classification
multiple-choice
intent-classification
customer-support
code
code-understanding
natural-language-inference
knowledge-distillation
cross-encoder
calibration
selective-prediction
falconsai
model-surgeon
attested-lineage
text-embeddings-inference
Model card Files Files and versions
xet
Community
1

Instructions to use Falconsai/proof_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Falconsai/proof_v2 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="Falconsai/proof_v2")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("Falconsai/proof_v2")
    model = AutoModel.from_pretrained("Falconsai/proof_v2", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
proof_v2 / encoder
600 MB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 1 commit
RealFalconsAI's picture
RealFalconsAI
Upload 9 files
9d9c228 verified about 18 hours ago
  • config.json
    1.25 kB
    Upload 9 files about 18 hours ago
  • model.safetensors
    596 MB
    xet
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  • special_tokens_map.json
    731 Bytes
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  • tokenizer.json
    3.58 MB
    Upload 9 files about 18 hours ago
  • tokenizer_config.json
    21.8 kB
    Upload 9 files about 18 hours ago