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mbayan
/
test-finetuned

Text Generation
Transformers
Safetensors
English
llama
text-generation-inference
unsloth
trl
sft
4-bit precision
bitsandbytes
Model card Files Files and versions
xet
Community

Instructions to use mbayan/test-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use mbayan/test-finetuned with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="mbayan/test-finetuned")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForCausalLM
    
    tokenizer = AutoTokenizer.from_pretrained("mbayan/test-finetuned")
    model = AutoModelForCausalLM.from_pretrained("mbayan/test-finetuned")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use mbayan/test-finetuned with vLLM:

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

    How to use mbayan/test-finetuned 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 "mbayan/test-finetuned" \
        --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": "mbayan/test-finetuned",
    		"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 "mbayan/test-finetuned" \
            --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": "mbayan/test-finetuned",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Unsloth Studio new

    How to use mbayan/test-finetuned 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 mbayan/test-finetuned 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 mbayan/test-finetuned to start chatting
    Using HuggingFace Spaces for Unsloth
    # No setup required
    # Open https://huggingface.co/spaces/unsloth/studio in your browser
    # Search for mbayan/test-finetuned to start chatting
    Load model with FastModel
    pip install unsloth
    from unsloth import FastModel
    model, tokenizer = FastModel.from_pretrained(
        model_name="mbayan/test-finetuned",
        max_seq_length=2048,
    )
  • Docker Model Runner

    How to use mbayan/test-finetuned with Docker Model Runner:

    docker model run hf.co/mbayan/test-finetuned

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  • .gitattributes
    1.52 kB
    initial commit almost 2 years ago
  • README.md
    579 Bytes
    Trained with Unsloth almost 2 years ago
  • config.json
    1.14 kB
    Trained with Unsloth almost 2 years ago
  • generation_config.json
    172 Bytes
    Trained with Unsloth almost 2 years ago
  • model-00001-of-00002.safetensors
    4.65 GB
    xet
    Trained with Unsloth almost 2 years ago
  • model-00002-of-00002.safetensors
    1.05 GB
    xet
    Trained with Unsloth almost 2 years ago
  • model.safetensors.index.json
    132 kB
    Trained with Unsloth almost 2 years ago
  • special_tokens_map.json
    464 Bytes
    Trained with Unsloth almost 2 years ago
  • tokenizer.json
    9.09 MB
    Trained with Unsloth almost 2 years ago
  • tokenizer_config.json
    50.6 kB
    Trained with Unsloth almost 2 years ago