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alexiaassis
/
Modelo-treinado

PEFT
Safetensors
llama-factory
lora
unsloth
Generated from Trainer
Model card Files Files and versions
xet
Community

Instructions to use alexiaassis/Modelo-treinado with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • PEFT

    How to use alexiaassis/Modelo-treinado with PEFT:

    from peft import PeftModel
    from transformers import AutoModelForCausalLM
    
    base_model = AutoModelForCausalLM.from_pretrained("unsloth/mistral-7b-instruct-v0.3-bnb-4bit")
    model = PeftModel.from_pretrained(base_model, "alexiaassis/Modelo-treinado")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • Unsloth Studio

    How to use alexiaassis/Modelo-treinado with Unsloth Studio:

    Install Unsloth Studio (macOS, Linux, WSL)
    curl -fsSL https://unsloth.ai/install.sh | sh
    # Run unsloth studio
    unsloth studio -H 0.0.0.0 -p 8888
    # Then open http://localhost:8888 in your browser
    # Search for alexiaassis/Modelo-treinado to start chatting
    Install Unsloth Studio (Windows)
    irm https://unsloth.ai/install.ps1 | iex
    # Run unsloth studio
    unsloth studio -H 0.0.0.0 -p 8888
    # Then open http://localhost:8888 in your browser
    # Search for alexiaassis/Modelo-treinado to start chatting
    Using HuggingFace Spaces for Unsloth
    # No setup required
    # Open https://huggingface.co/spaces/unsloth/studio in your browser
    # Search for alexiaassis/Modelo-treinado to start chatting
    Load model with FastModel
    pip install unsloth
    from unsloth import FastModel
    model, tokenizer = FastModel.from_pretrained(
        model_name="alexiaassis/Modelo-treinado",
        max_seq_length=2048,
    )
Modelo-treinado / checkpoint-1395
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  • 1 contributor
History: 1 commit
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alexiaassis
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6ce1151 verified 10 months ago
  • README.md
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  • adapter_config.json
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  • adapter_model.safetensors
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  • chat_template.jinja
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  • optimizer.pt
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  • rng_state.pth
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  • scaler.pt
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  • scheduler.pt
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  • special_tokens_map.json
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  • tokenizer.json
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  • tokenizer.model
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  • tokenizer_config.json
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  • trainer_state.json
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  • training_args.bin
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