Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing
    • Website
      • Tasks
      • HuggingChat
      • Collections
      • Languages
      • Organizations
    • Community
      • Blog
      • Posts
      • Daily Papers
      • Hardware
      • Learn
      • Discord
      • Forum
      • GitHub
    • Solutions
      • Team & Enterprise
      • Hugging Face PRO
      • Enterprise Support
      • Inference Providers
      • Inference Endpoints
      • Storage Buckets

  • Log In
  • Sign Up

runtime-contracts
/
llama31-8b-knapsack-lora-persistent

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

Instructions to use runtime-contracts/llama31-8b-knapsack-lora-persistent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • PEFT

    How to use runtime-contracts/llama31-8b-knapsack-lora-persistent with PEFT:

    from peft import PeftModel
    from transformers import AutoModelForCausalLM
    
    base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.1-8B")
    model = PeftModel.from_pretrained(base_model, "runtime-contracts/llama31-8b-knapsack-lora-persistent")
  • Transformers

    How to use runtime-contracts/llama31-8b-knapsack-lora-persistent with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="runtime-contracts/llama31-8b-knapsack-lora-persistent")
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("runtime-contracts/llama31-8b-knapsack-lora-persistent", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • vLLM

    How to use runtime-contracts/llama31-8b-knapsack-lora-persistent with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "runtime-contracts/llama31-8b-knapsack-lora-persistent"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "runtime-contracts/llama31-8b-knapsack-lora-persistent",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/runtime-contracts/llama31-8b-knapsack-lora-persistent
  • SGLang

    How to use runtime-contracts/llama31-8b-knapsack-lora-persistent 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 "runtime-contracts/llama31-8b-knapsack-lora-persistent" \
        --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": "runtime-contracts/llama31-8b-knapsack-lora-persistent",
    		"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 "runtime-contracts/llama31-8b-knapsack-lora-persistent" \
            --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": "runtime-contracts/llama31-8b-knapsack-lora-persistent",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use runtime-contracts/llama31-8b-knapsack-lora-persistent with Docker Model Runner:

    docker model run hf.co/runtime-contracts/llama31-8b-knapsack-lora-persistent
llama31-8b-knapsack-lora-persistent
688 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 4 commits
TieuDaoChanNhan's picture
TieuDaoChanNhan
Add Llama 3.1 Community License
5777370 verified 12 days ago
  • .gitattributes
    1.57 kB
    Add files 13 days ago
  • LICENSE
    7.63 kB
    Add Llama 3.1 Community License 12 days ago
  • README.md
    2.54 kB
    Update card: license, paper reference 12 days ago
  • adapter_config.json
    1.15 kB
    Add files 13 days ago
  • adapter_model.safetensors
    671 MB
    xet
    Add files 13 days ago
  • special_tokens_map.json
    459 Bytes
    Add files 13 days ago
  • tokenizer.json
    17.2 MB
    xet
    Add files 13 days ago
  • tokenizer_config.json
    50.6 kB
    Add files 13 days ago