Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing

  • Log In
  • Sign Up

finalform
/
foamMetaLLama3.1-8B-Instruct

Text Generation
PEFT
TensorBoard
Safetensors
Transformers
lora
sft
trl
conversational
Model card Files Files and versions
xet
Metrics Training metrics Community

Instructions to use finalform/foamMetaLLama3.1-8B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • PEFT

    How to use finalform/foamMetaLLama3.1-8B-Instruct with PEFT:

    from peft import PeftModel
    from transformers import AutoModelForCausalLM
    
    base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.1-8B-Instruct")
    model = PeftModel.from_pretrained(base_model, "finalform/foamMetaLLama3.1-8B-Instruct")
  • Transformers

    How to use finalform/foamMetaLLama3.1-8B-Instruct with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="finalform/foamMetaLLama3.1-8B-Instruct")
    messages = [
        {"role": "user", "content": "Who are you?"},
    ]
    pipe(messages)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("finalform/foamMetaLLama3.1-8B-Instruct", dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use finalform/foamMetaLLama3.1-8B-Instruct with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "finalform/foamMetaLLama3.1-8B-Instruct"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "finalform/foamMetaLLama3.1-8B-Instruct",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/finalform/foamMetaLLama3.1-8B-Instruct
  • SGLang

    How to use finalform/foamMetaLLama3.1-8B-Instruct 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 "finalform/foamMetaLLama3.1-8B-Instruct" \
        --host 0.0.0.0 \
        --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "finalform/foamMetaLLama3.1-8B-Instruct",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    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 "finalform/foamMetaLLama3.1-8B-Instruct" \
            --host 0.0.0.0 \
            --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "finalform/foamMetaLLama3.1-8B-Instruct",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
  • Docker Model Runner

    How to use finalform/foamMetaLLama3.1-8B-Instruct with Docker Model Runner:

    docker model run hf.co/finalform/foamMetaLLama3.1-8B-Instruct
foamMetaLLama3.1-8B-Instruct
1.02 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
finalform's picture
finalform
Upload folder using huggingface_hub
e865b3b verified 9 months ago
  • Aug20_03-24-47_209-20-159-65
    Upload folder using huggingface_hub 9 months ago
  • Aug20_05-06-11_209-20-159-65
    Upload folder using huggingface_hub 9 months ago
  • .gitattributes
    1.57 kB
    Upload folder using huggingface_hub 9 months ago
  • README.md
    5.23 kB
    Upload folder using huggingface_hub 9 months ago
  • adapter_config.json
    943 Bytes
    Upload folder using huggingface_hub 9 months ago
  • adapter_model.safetensors
    336 MB
    xet
    Upload folder using huggingface_hub 9 months ago
  • chat_template.jinja
    4.61 kB
    Upload folder using huggingface_hub 9 months ago
  • optimizer.pt
    671 MB
    xet
    Upload folder using huggingface_hub 9 months ago
  • rng_state.pth
    14.6 kB
    xet
    Upload folder using huggingface_hub 9 months ago
  • scheduler.pt
    1.47 kB
    xet
    Upload folder using huggingface_hub 9 months ago
  • special_tokens_map.json
    325 Bytes
    Upload folder using huggingface_hub 9 months ago
  • tokenizer.json
    17.2 MB
    xet
    Upload folder using huggingface_hub 9 months ago
  • tokenizer_config.json
    50.6 kB
    Upload folder using huggingface_hub 9 months ago
  • trainer_state.json
    23.3 kB
    Upload folder using huggingface_hub 9 months ago
  • training_args.bin
    6.03 kB
    xet
    Upload folder using huggingface_hub 9 months ago