Text Generation
Safetensors
GGUF
German
llama
philosophie
gott
kant
religion
lebensratschläge
bibel
koran
hinduismus
buddhismus
christentum
ratschläge
esoterik
platon
spiritualität
Alexander Schönau (creator)
conversational
Instructions to use Alex-Linguist/AllwissenGPT-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Alex-Linguist/AllwissenGPT-7B 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 Alex-Linguist/AllwissenGPT-7B # Run inference directly in the terminal: llama cli -hf Alex-Linguist/AllwissenGPT-7B
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Alex-Linguist/AllwissenGPT-7B # Run inference directly in the terminal: llama cli -hf Alex-Linguist/AllwissenGPT-7B
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 Alex-Linguist/AllwissenGPT-7B # Run inference directly in the terminal: ./llama-cli -hf Alex-Linguist/AllwissenGPT-7B
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 Alex-Linguist/AllwissenGPT-7B # Run inference directly in the terminal: ./build/bin/llama-cli -hf Alex-Linguist/AllwissenGPT-7B
Use Docker
docker model run hf.co/Alex-Linguist/AllwissenGPT-7B
- LM Studio
- Jan
- vLLM
How to use Alex-Linguist/AllwissenGPT-7B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Alex-Linguist/AllwissenGPT-7B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Alex-Linguist/AllwissenGPT-7B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Alex-Linguist/AllwissenGPT-7B
- Ollama
How to use Alex-Linguist/AllwissenGPT-7B with Ollama:
ollama run hf.co/Alex-Linguist/AllwissenGPT-7B
- Unsloth Desktop
- Pi
How to use Alex-Linguist/AllwissenGPT-7B with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Alex-Linguist/AllwissenGPT-7B
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "Alex-Linguist/AllwissenGPT-7B" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use Alex-Linguist/AllwissenGPT-7B with Docker Model Runner:
docker model run hf.co/Alex-Linguist/AllwissenGPT-7B
- Lemonade
How to use Alex-Linguist/AllwissenGPT-7B with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Alex-Linguist/AllwissenGPT-7B
Run and chat with the model
lemonade run user.AllwissenGPT-7B-{{QUANT_TAG}}List all available models
lemonade list
- Hermes Agent
How to use Alex-Linguist/AllwissenGPT-7B with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Alex-Linguist/AllwissenGPT-7B
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 Alex-Linguist/AllwissenGPT-7B
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use Alex-Linguist/AllwissenGPT-7B with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Alex-Linguist/AllwissenGPT-7B
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 "Alex-Linguist/AllwissenGPT-7B" \ --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"
Download config.json from Alex-Linguist/AllwissenGPT-7B: direct link, hf CLI and curl.
- Browser
- Download file 1.01 kB
-
https://huggingface.co/Alex-Linguist/AllwissenGPT-7B/resolve/main/config.json
- Command line
-
hf download hf://Alex-Linguist/AllwissenGPT-7B/config.json
-
curl -L -o config.json https://huggingface.co/Alex-Linguist/AllwissenGPT-7B/resolve/main/config.json
1.01 kB
| { | |
| "architectures": [ | |
| "LlamaForCausalLM" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 128000, | |
| "torch_dtype": "bfloat16", | |
| "eos_token_id": 128009, | |
| "head_dim": 128, | |
| "hidden_act": "silu", | |
| "hidden_size": 4096, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 14336, | |
| "max_position_embeddings": 131072, | |
| "mlp_bias": false, | |
| "model_type": "llama", | |
| "num_attention_heads": 32, | |
| "num_hidden_layers": 32, | |
| "num_key_value_heads": 8, | |
| "pad_token_id": 128004, | |
| "pretraining_tp": 1, | |
| "rms_norm_eps": 1e-05, | |
| "rope_scaling": { | |
| "factor": 8.0, | |
| "high_freq_factor": 4.0, | |
| "low_freq_factor": 1.0, | |
| "original_max_position_embeddings": 8192, | |
| "rope_type": "llama3" | |
| }, | |
| "rope_theta": 500000.0, | |
| "tie_word_embeddings": false, | |
| "transformers_version": "4.57.3", | |
| "unsloth_fixed": true, | |
| "unsloth_version": "2025.12.8", | |
| "use_cache": true, | |
| "vocab_size": 128256 | |
| } |