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GGUF
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deepnarra_paham_experimental
deepnarra
paham-experimental
awake-continuum
3-tier-learning
qlora
fast-weights
92-experts
h-moe
bitnet-b158
tq1_0
conversational
Instructions to use DeepNarra/Paham-Experimental 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 DeepNarra/Paham-Experimental 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 DeepNarra/Paham-Experimental:TQ1_0 # Run inference directly in the terminal: llama cli -hf DeepNarra/Paham-Experimental:TQ1_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf DeepNarra/Paham-Experimental:TQ1_0 # Run inference directly in the terminal: llama cli -hf DeepNarra/Paham-Experimental:TQ1_0
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 DeepNarra/Paham-Experimental:TQ1_0 # Run inference directly in the terminal: ./llama-cli -hf DeepNarra/Paham-Experimental:TQ1_0
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 DeepNarra/Paham-Experimental:TQ1_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf DeepNarra/Paham-Experimental:TQ1_0
Use Docker
docker model run hf.co/DeepNarra/Paham-Experimental:TQ1_0
- Llama new
- LM Studio
- Jan
- vLLM
How to use DeepNarra/Paham-Experimental with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "DeepNarra/Paham-Experimental" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "DeepNarra/Paham-Experimental", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/DeepNarra/Paham-Experimental:TQ1_0
- Ollama
How to use DeepNarra/Paham-Experimental with Ollama:
ollama run hf.co/DeepNarra/Paham-Experimental:TQ1_0
- Unsloth Desktop
- Docker Model Runner
How to use DeepNarra/Paham-Experimental with Docker Model Runner:
docker model run hf.co/DeepNarra/Paham-Experimental:TQ1_0
- Lemonade
How to use DeepNarra/Paham-Experimental with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull DeepNarra/Paham-Experimental:TQ1_0
Run and chat with the model
lemonade run user.Paham-Experimental-TQ1_0
List all available models
lemonade list
- Atomic Chat
Download tokenizer.json from DeepNarra/Paham-Experimental: direct link, hf CLI and curl.
- Browser
- Download file 3.16 MB
-
https://huggingface.co/DeepNarra/Paham-Experimental/resolve/main/tokenizer.json
- Command line
-
hf download hf://DeepNarra/Paham-Experimental/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/DeepNarra/Paham-Experimental/resolve/main/tokenizer.json
3.16 MB
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