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build-small-hackathon
/
figment-finetuned-model-archive

Text Generation
Transformers
Safetensors
GGUF
PEFT
English
figment
lora
v1
v2
v3
v4
v5
v6
v7
v8
v9
v10
v11
v12
v13
v14p
protocol-navigation
synthetic-data
not-for-clinical-use
conversational
Model card Files Files and versions
xet
Community

Instructions to use build-small-hackathon/figment-finetuned-model-archive with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use build-small-hackathon/figment-finetuned-model-archive with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="build-small-hackathon/figment-finetuned-model-archive")
    messages = [
        {"role": "user", "content": "Who are you?"},
    ]
    pipe(messages)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("build-small-hackathon/figment-finetuned-model-archive", dtype="auto")
  • PEFT

    How to use build-small-hackathon/figment-finetuned-model-archive with PEFT:

    Task type is invalid.
  • llama-cpp-python

    How to use build-small-hackathon/figment-finetuned-model-archive with llama-cpp-python:

    # !pip install llama-cpp-python
    
    from llama_cpp import Llama
    
    llm = Llama.from_pretrained(
    	repo_id="build-small-hackathon/figment-finetuned-model-archive",
    	filename="figment_sft_v10/figment-sft-v10-lora-merged-bf16.bf16.gguf",
    )
    
    llm.create_chat_completion(
    	messages = [
    		{
    			"role": "user",
    			"content": "What is the capital of France?"
    		}
    	]
    )
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • llama.cpp

    How to use build-small-hackathon/figment-finetuned-model-archive with llama.cpp:

    Install (macOS, Linux)
    curl -LsSf https://llama.app/install.sh | sh
    # Start a local OpenAI-compatible server with a web UI:
    llama serve -hf build-small-hackathon/figment-finetuned-model-archive:BF16
    # Run inference directly in the terminal:
    llama cli -hf build-small-hackathon/figment-finetuned-model-archive:BF16
    Install from WinGet (Windows)
    winget install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama serve -hf build-small-hackathon/figment-finetuned-model-archive:BF16
    # Run inference directly in the terminal:
    llama cli -hf build-small-hackathon/figment-finetuned-model-archive:BF16
    Use pre-built binary
    # Download pre-built binary from:
    # https://github.com/ggerganov/llama.cpp/releases
    # Start a local OpenAI-compatible server with a web UI:
    ./llama-server -hf build-small-hackathon/figment-finetuned-model-archive:BF16
    # Run inference directly in the terminal:
    ./llama-cli -hf build-small-hackathon/figment-finetuned-model-archive:BF16
    Build from source code
    git clone https://github.com/ggerganov/llama.cpp.git
    cd llama.cpp
    cmake -B build
    cmake --build build -j --target llama-server llama-cli
    # Start a local OpenAI-compatible server with a web UI:
    ./build/bin/llama-server -hf build-small-hackathon/figment-finetuned-model-archive:BF16
    # Run inference directly in the terminal:
    ./build/bin/llama-cli -hf build-small-hackathon/figment-finetuned-model-archive:BF16
    Use Docker
    docker model run hf.co/build-small-hackathon/figment-finetuned-model-archive:BF16
  • LM Studio
  • Jan
  • vLLM

    How to use build-small-hackathon/figment-finetuned-model-archive with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "build-small-hackathon/figment-finetuned-model-archive"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "build-small-hackathon/figment-finetuned-model-archive",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/build-small-hackathon/figment-finetuned-model-archive:BF16
  • SGLang

    How to use build-small-hackathon/figment-finetuned-model-archive 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 "build-small-hackathon/figment-finetuned-model-archive" \
        --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": "build-small-hackathon/figment-finetuned-model-archive",
    		"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 "build-small-hackathon/figment-finetuned-model-archive" \
            --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": "build-small-hackathon/figment-finetuned-model-archive",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
  • Ollama

    How to use build-small-hackathon/figment-finetuned-model-archive with Ollama:

    ollama run hf.co/build-small-hackathon/figment-finetuned-model-archive:BF16
  • Unsloth Studio

    How to use build-small-hackathon/figment-finetuned-model-archive 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 build-small-hackathon/figment-finetuned-model-archive 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 build-small-hackathon/figment-finetuned-model-archive to start chatting
    Using HuggingFace Spaces for Unsloth
    # No setup required
    # Open https://huggingface.co/spaces/unsloth/studio in your browser
    # Search for build-small-hackathon/figment-finetuned-model-archive to start chatting
  • Pi

    How to use build-small-hackathon/figment-finetuned-model-archive with Pi:

    Start the llama.cpp server
    # Install llama.cpp:
    brew install llama.cpp
    # Start a local OpenAI-compatible server:
    llama serve -hf build-small-hackathon/figment-finetuned-model-archive:BF16
    Configure the model in Pi
    # Install Pi:
    npm install -g @mariozechner/pi-coding-agent
    # Add to ~/.pi/agent/models.json:
    {
      "providers": {
        "llama-cpp": {
          "baseUrl": "http://localhost:8080/v1",
          "api": "openai-completions",
          "apiKey": "none",
          "models": [
            {
              "id": "build-small-hackathon/figment-finetuned-model-archive:BF16"
            }
          ]
        }
      }
    }
    Run Pi
    # Start Pi in your project directory:
    pi
  • Hermes Agent new

    How to use build-small-hackathon/figment-finetuned-model-archive with Hermes Agent:

    Start the llama.cpp server
    # Install llama.cpp:
    brew install llama.cpp
    # Start a local OpenAI-compatible server:
    llama serve -hf build-small-hackathon/figment-finetuned-model-archive:BF16
    Configure Hermes
    # Install Hermes:
    curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
    hermes setup
    # Point Hermes at the local server:
    hermes config set model.provider custom
    hermes config set model.base_url http://127.0.0.1:8080/v1
    hermes config set model.default build-small-hackathon/figment-finetuned-model-archive:BF16
    Run Hermes
    hermes
  • Atomic Chat new
  • OpenClaw new

    How to use build-small-hackathon/figment-finetuned-model-archive with OpenClaw:

    Start the llama.cpp server
    # Install llama.cpp:
    brew install llama.cpp
    # Start a local OpenAI-compatible server:
    llama serve -hf build-small-hackathon/figment-finetuned-model-archive:BF16
    Configure OpenClaw
    # Install OpenClaw:
    npm install -g openclaw@latest
    # Register the local server and set it as the default model:
    openclaw onboard --non-interactive --mode local \
      --auth-choice custom-api-key \
      --custom-base-url http://127.0.0.1:8080/v1 \
      --custom-model-id "build-small-hackathon/figment-finetuned-model-archive:BF16" \
      --custom-provider-id llama-cpp \
      --custom-compatibility openai \
      --custom-text-input \
      --accept-risk \
      --skip-health
    Run OpenClaw
    openclaw agent --local --agent main --message "Hello from Hugging Face"
  • Docker Model Runner

    How to use build-small-hackathon/figment-finetuned-model-archive with Docker Model Runner:

    docker model run hf.co/build-small-hackathon/figment-finetuned-model-archive:BF16
  • Lemonade

    How to use build-small-hackathon/figment-finetuned-model-archive with Lemonade:

    Pull the model
    # Download Lemonade from https://lemonade-server.ai/
    lemonade pull build-small-hackathon/figment-finetuned-model-archive:BF16
    Run and chat with the model
    lemonade run user.figment-finetuned-model-archive-BF16
    List all available models
    lemonade list
figment-finetuned-model-archive
215 GB
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  • 1 contributor
History: 50 commits
ThomsenDrake's picture
ThomsenDrake
Document Figment SFT v1 pilot archive
7da772e verified 23 days ago
  • figment_sft_v1
    Upload Figment SFT v1 pilot merged BF16 checkpoint 23 days ago
  • figment_sft_v10
    Upload Figment SFT v10 GGUF sidecar 24 days ago
  • figment_sft_v11
    Upload Figment SFT v11 GGUF sidecar 24 days ago
  • figment_sft_v12
    Upload Figment SFT v12 GGUF sidecar 24 days ago
  • figment_sft_v13
    Upload Figment SFT v13 GGUF sidecar 24 days ago
  • figment_sft_v14p
    Upload Figment SFT v14p GGUF sidecar 24 days ago
  • figment_sft_v5
    Upload Figment SFT v5 GGUF sidecar 25 days ago
  • figment_sft_v6
    Upload Figment SFT v6 GGUF sidecar 25 days ago
  • figment_sft_v7
    Upload Figment SFT v7 GGUF sidecar 25 days ago
  • figment_sft_v8
    Upload Figment SFT v8 GGUF sidecar 24 days ago
  • figment_sft_v9
    Upload Figment SFT v9 GGUF sidecar 24 days ago
  • v2-20260609-merged-bf16
    Restore Figment v2 BF16 shard 2 26 days ago
  • v3-20260610-merged-bf16
    Restore Figment v3 BF16 shard 2 26 days ago
  • v4-20260611-merged-bf16
    Restore v4 tokenizer after cleanup 26 days ago
  • .gitattributes
    4.26 kB
    Upload Figment SFT v1 pilot merged BF16 checkpoint 23 days ago
  • README.md
    23.8 kB
    Document Figment SFT v1 pilot archive 23 days ago
  • v2-20260609-merged-bf16.gguf
    7.96 GB
    LFS
    Restore Figment v2 GGUF 26 days ago
  • v3-20260610-merged-bf16.gguf
    7.96 GB
    LFS
    Restore Figment v3 GGUF 26 days ago
  • v4-20260611-merged-bf16.gguf
    7.96 GB
    xet
    Add Figment v4 merged BF16 GGUF 26 days ago