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Truthseeker87
/
solarhive-e4b-gguf

Image-Text-to-Text
GGUF
English
gemma4
llama-cpp
ollama
llama-server
multimodal
function-calling
solar-energy
community-solar
lora
unsloth
edge-ai
energy
sustainability
hackathon
Eval Results (legacy)
conversational
Model card Files Files and versions
xet
Community

Instructions to use Truthseeker87/solarhive-e4b-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • llama-cpp-python

    How to use Truthseeker87/solarhive-e4b-gguf with llama-cpp-python:

    # !pip install llama-cpp-python
    
    from llama_cpp import Llama
    
    llm = Llama.from_pretrained(
    	repo_id="Truthseeker87/solarhive-e4b-gguf",
    	filename="mmproj-solarhive-e4b-BF16.gguf",
    )
    
    llm.create_chat_completion(
    	messages = [
    		{
    			"role": "user",
    			"content": [
    				{
    					"type": "text",
    					"text": "Describe this image in one sentence."
    				},
    				{
    					"type": "image_url",
    					"image_url": {
    						"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
    					}
    				}
    			]
    		}
    	]
    )
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • llama.cpp

    How to use Truthseeker87/solarhive-e4b-gguf with llama.cpp:

    Install from brew
    brew install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama-server -hf Truthseeker87/solarhive-e4b-gguf:BF16
    # Run inference directly in the terminal:
    llama-cli -hf Truthseeker87/solarhive-e4b-gguf:BF16
    Install from WinGet (Windows)
    winget install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama-server -hf Truthseeker87/solarhive-e4b-gguf:BF16
    # Run inference directly in the terminal:
    llama-cli -hf Truthseeker87/solarhive-e4b-gguf: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 Truthseeker87/solarhive-e4b-gguf:BF16
    # Run inference directly in the terminal:
    ./llama-cli -hf Truthseeker87/solarhive-e4b-gguf: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 Truthseeker87/solarhive-e4b-gguf:BF16
    # Run inference directly in the terminal:
    ./build/bin/llama-cli -hf Truthseeker87/solarhive-e4b-gguf:BF16
    Use Docker
    docker model run hf.co/Truthseeker87/solarhive-e4b-gguf:BF16
  • LM Studio
  • Jan
  • vLLM

    How to use Truthseeker87/solarhive-e4b-gguf with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "Truthseeker87/solarhive-e4b-gguf"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "Truthseeker87/solarhive-e4b-gguf",
    		"messages": [
    			{
    				"role": "user",
    				"content": [
    					{
    						"type": "text",
    						"text": "Describe this image in one sentence."
    					},
    					{
    						"type": "image_url",
    						"image_url": {
    							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
    						}
    					}
    				]
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/Truthseeker87/solarhive-e4b-gguf:BF16
  • Ollama

    How to use Truthseeker87/solarhive-e4b-gguf with Ollama:

    ollama run hf.co/Truthseeker87/solarhive-e4b-gguf:BF16
  • Unsloth Studio

    How to use Truthseeker87/solarhive-e4b-gguf 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 Truthseeker87/solarhive-e4b-gguf 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 Truthseeker87/solarhive-e4b-gguf to start chatting
    Using HuggingFace Spaces for Unsloth
    # No setup required
    # Open https://huggingface.co/spaces/unsloth/studio in your browser
    # Search for Truthseeker87/solarhive-e4b-gguf to start chatting
  • Pi

    How to use Truthseeker87/solarhive-e4b-gguf with Pi:

    Start the llama.cpp server
    # Install llama.cpp:
    brew install llama.cpp
    # Start a local OpenAI-compatible server:
    llama-server -hf Truthseeker87/solarhive-e4b-gguf: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": "Truthseeker87/solarhive-e4b-gguf:BF16"
            }
          ]
        }
      }
    }
    Run Pi
    # Start Pi in your project directory:
    pi
  • Hermes Agent new

    How to use Truthseeker87/solarhive-e4b-gguf with Hermes Agent:

    Start the llama.cpp server
    # Install llama.cpp:
    brew install llama.cpp
    # Start a local OpenAI-compatible server:
    llama-server -hf Truthseeker87/solarhive-e4b-gguf: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 Truthseeker87/solarhive-e4b-gguf:BF16
    Run Hermes
    hermes
  • Docker Model Runner

    How to use Truthseeker87/solarhive-e4b-gguf with Docker Model Runner:

    docker model run hf.co/Truthseeker87/solarhive-e4b-gguf:BF16
  • Lemonade

    How to use Truthseeker87/solarhive-e4b-gguf with Lemonade:

    Pull the model
    # Download Lemonade from https://lemonade-server.ai/
    lemonade pull Truthseeker87/solarhive-e4b-gguf:BF16
    Run and chat with the model
    lemonade run user.solarhive-e4b-gguf-BF16
    List all available models
    lemonade list
solarhive-e4b-gguf
Ctrl+K
Ctrl+K
  • 1 contributor
History: 16 commits
Truthseeker87's picture
Truthseeker87
README: scope-lock MTP as future iteration
e7f9a17 verified 19 days ago
  • .gitattributes
    1.8 kB
    Add PLE-Q4_0 Q4_K_M text variant (4.61 GB, laptop-produced, 10/10 benchmark) about 1 month ago
  • LICENSE
    1.37 kB
    Add model card, Modelfiles, LICENSE, banner image about 1 month ago
  • Modelfile
    419 Bytes
    Add model card, Modelfiles, LICENSE, banner image about 1 month ago
  • Modelfile.standard
    428 Bytes
    Add model card, Modelfiles, LICENSE, banner image about 1 month ago
  • README.md
    44.2 kB
    README: scope-lock MTP as future iteration 19 days ago
  • SolarHive_HeaderImage_1920x1080_HFModelCard.png
    758 kB
    xet
    Add model card, Modelfiles, LICENSE, banner image about 1 month ago
  • mmproj-solarhive-e4b-BF16.gguf
    992 MB
    xet
    Add mmproj companion (vision SigLIP + audio Conformer, 1411 tensors) about 1 month ago
  • solarhive-e4b-q4_k_m-standard.gguf
    5.34 GB
    xet
    Add Unsloth-standard Q4_K_M (PLE Q6_K) — produced on Colab Pro High-RAM about 1 month ago
  • solarhive-e4b-q4_k_m.gguf
    5.34 GB
    xet
    Upload solarhive-e4b-q4_k_m.gguf with huggingface_hub about 1 month ago