Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing

  • Log In
  • Sign Up

Rakancorle1
/
ThinkGuard

Text Classification
Transformers
TensorBoard
Safetensors
English
llama
text-generation
llama-factory
full
Generated from Trainer
text-embeddings-inference
Model card Files Files and versions
xet
Metrics Training metrics Community
1

Instructions to use Rakancorle1/ThinkGuard with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Rakancorle1/ThinkGuard with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="Rakancorle1/ThinkGuard")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForCausalLM
    
    tokenizer = AutoTokenizer.from_pretrained("Rakancorle1/ThinkGuard")
    model = AutoModelForCausalLM.from_pretrained("Rakancorle1/ThinkGuard")
  • Notebooks
  • Google Colab
  • Kaggle
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

Question Regarding Fine-tuning Format Used in ThinkGuard (LLaMA Factory?)

1
#1 opened about 1 year ago by
WANNTING
Company
TOS Privacy About Careers
Website
Models Datasets Spaces Pricing Docs