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bpavlsh
/
Mistral-Fake-News-Detection

Summarization
PEFT
Safetensors
fake news detection
propaganda
fake news
propaganda detection
manipulative constructions analysis
offensive language analysis
text-generation
Model card Files Files and versions
xet
Community

Instructions to use bpavlsh/Mistral-Fake-News-Detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • PEFT

    How to use bpavlsh/Mistral-Fake-News-Detection with PEFT:

    from peft import PeftModel
    from transformers import AutoModelForCausalLM
    
    base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.1")
    model = PeftModel.from_pretrained(base_model, "bpavlsh/Mistral-Fake-News-Detection")
  • Notebooks
  • Google Colab
  • Kaggle
Mistral-Fake-News-Detection
440 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 17 commits
bpavlsh's picture
bpavlsh
Update README.md
40c1db0 verified 9 months ago
  • .gitattributes
    1.52 kB
    initial commit 12 months ago
  • README.md
    2.79 kB
    Update README.md 9 months ago
  • adapter_config.json
    791 Bytes
    Upload 8 files 12 months ago
  • adapter_model.safetensors
    436 MB
    xet
    Upload 8 files 12 months ago
  • chat_template.jinja
    1.06 kB
    Upload 8 files 12 months ago
  • special_tokens_map.json
    414 Bytes
    Upload 8 files 12 months ago
  • tokenizer.json
    3.51 MB
    Upload 8 files 12 months ago
  • tokenizer.model
    493 kB
    xet
    Upload 8 files 12 months ago
  • tokenizer_config.json
    1.03 kB
    Upload 8 files 12 months ago