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Skskskd
/
Lumen-Fine-tuning

Text Generation
PEFT
Safetensors
Transformers
Portuguese
lora
Model card Files Files and versions
xet
Community

Instructions to use Skskskd/Lumen-Fine-tuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • PEFT

    How to use Skskskd/Lumen-Fine-tuning with PEFT:

    from peft import PeftModel
    from transformers import AutoModelForCausalLM
    
    base_model = AutoModelForCausalLM.from_pretrained("unsloth/qwen3-4b-base")
    model = PeftModel.from_pretrained(base_model, "Skskskd/Lumen-Fine-tuning")
  • Transformers

    How to use Skskskd/Lumen-Fine-tuning with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="Skskskd/Lumen-Fine-tuning")
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("Skskskd/Lumen-Fine-tuning", dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • vLLM

    How to use Skskskd/Lumen-Fine-tuning with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "Skskskd/Lumen-Fine-tuning"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "Skskskd/Lumen-Fine-tuning",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/Skskskd/Lumen-Fine-tuning
  • SGLang

    How to use Skskskd/Lumen-Fine-tuning with SGLang:

    Install from pip and serve model
    # Install SGLang from pip:
    pip install sglang
    # Start the SGLang server:
    python3 -m sglang.launch_server \
        --model-path "Skskskd/Lumen-Fine-tuning" \
        --host 0.0.0.0 \
        --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "Skskskd/Lumen-Fine-tuning",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker images
    docker run --gpus all \
        --shm-size 32g \
        -p 30000:30000 \
        -v ~/.cache/huggingface:/root/.cache/huggingface \
        --env "HF_TOKEN=<secret>" \
        --ipc=host \
        lmsysorg/sglang:latest \
        python3 -m sglang.launch_server \
            --model-path "Skskskd/Lumen-Fine-tuning" \
            --host 0.0.0.0 \
            --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "Skskskd/Lumen-Fine-tuning",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use Skskskd/Lumen-Fine-tuning with Docker Model Runner:

    docker model run hf.co/Skskskd/Lumen-Fine-tuning
Lumen-Fine-tuning
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  • 1 contributor
History: 3 commits
Skskskd's picture
Skskskd
Update README.md
ce9ff4d verified 2 days ago
  • checkpoint-38
    LoRA v1 - Unsloth + SFTTrainer (SEM bitsandbytes) 3 days ago
  • checkpoint-57
    LoRA v1 - Unsloth + SFTTrainer (SEM bitsandbytes) 3 days ago
  • .gitattributes
    1.7 kB
    LoRA v1 - Unsloth + SFTTrainer (SEM bitsandbytes) 3 days ago
  • README.md
    1.62 kB
    Update README.md 2 days ago
  • adapter_config.json
    1.24 kB
    LoRA v1 - Unsloth + SFTTrainer (SEM bitsandbytes) 3 days ago
  • adapter_model.safetensors
    132 MB
    xet
    LoRA v1 - Unsloth + SFTTrainer (SEM bitsandbytes) 3 days ago
  • tokenizer.json
    11.4 MB
    xet
    LoRA v1 - Unsloth + SFTTrainer (SEM bitsandbytes) 3 days ago
  • tokenizer_config.json
    5.1 kB
    LoRA v1 - Unsloth + SFTTrainer (SEM bitsandbytes) 3 days ago
  • training_args.bin

    Detected Pickle imports (10)

    • "torch.device",
    • "transformers.trainer_utils.SchedulerType",
    • "UnslothSFTTrainer.UnslothSFTConfig",
    • "transformers.trainer_utils.IntervalStrategy",
    • "accelerate.state.PartialState",
    • "transformers.trainer_utils.SaveStrategy",
    • "transformers.trainer_pt_utils.AcceleratorConfig",
    • "transformers.training_args.OptimizerNames",
    • "transformers.trainer_utils.HubStrategy",
    • "accelerate.utils.dataclasses.DistributedType"

    How to fix it?

    5.78 kB
    xet
    LoRA v1 - Unsloth + SFTTrainer (SEM bitsandbytes) 3 days ago
  • unsloth_config.json
    281 Bytes
    LoRA v1 - Unsloth + SFTTrainer (SEM bitsandbytes) 3 days ago