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mwill-AImission
/
SecureCLI-Tuner-V2

Text Generation
PEFT
Safetensors
English
axolotl
qlora
code-generation
bash
cli
security
devops
conversational
Model card Files Files and versions
xet
Community

Instructions to use mwill-AImission/SecureCLI-Tuner-V2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • PEFT

    How to use mwill-AImission/SecureCLI-Tuner-V2 with PEFT:

    from peft import PeftModel
    from transformers import AutoModelForCausalLM
    
    base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-Coder-7B-Instruct")
    model = PeftModel.from_pretrained(base_model, "mwill-AImission/SecureCLI-Tuner-V2")
  • Notebooks
  • Google Colab
  • Kaggle
SecureCLI-Tuner-V2
53.7 MB
Ctrl+K
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  • 1 contributor
History: 9 commits
mwill-AImission's picture
mwill-AImission
Update README.md
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  • .gitattributes
    1.63 kB
    Upload SecureCLI-Tuner_image.png 5 months ago
  • README.md
    10.2 kB
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  • SecureCLI-Tuner_image.png
    7.05 MB
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  • adapter_config.json
    1.01 kB
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  • adapter_model.safetensors
    20.2 MB
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  • added_tokens.json
    605 Bytes
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  • chat_template.jinja
    2.51 kB
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  • merges.txt
    1.67 MB
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  • optimizer.pt
    10.5 MB
    xet
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  • rng_state.pth
    14.2 kB
    xet
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  • scheduler.pt
    1.06 kB
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  • special_tokens_map.json
    613 Bytes
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  • tokenizer.json
    11.4 MB
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  • tokenizer_config.json
    4.69 kB
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  • trainer_state.json
    11.8 kB
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  • training_args.bin
    6.52 kB
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  • vocab.json
    2.78 MB
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