Instructions to use minkdank/LLAMA-JSON-data-extration 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 minkdank/LLAMA-JSON-data-extration 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 minkdank/LLAMA-JSON-data-extration:Q4_K_M # Run inference directly in the terminal: llama cli -hf minkdank/LLAMA-JSON-data-extration:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf minkdank/LLAMA-JSON-data-extration:Q4_K_M # Run inference directly in the terminal: llama cli -hf minkdank/LLAMA-JSON-data-extration:Q4_K_M
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf minkdank/LLAMA-JSON-data-extration:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf minkdank/LLAMA-JSON-data-extration:Q4_K_M
Use Docker
docker model run hf.co/minkdank/LLAMA-JSON-data-extration:Q4_K_M
- Llama new
- LM Studio
- Jan
- Ollama
How to use minkdank/LLAMA-JSON-data-extration with Ollama:
ollama run hf.co/minkdank/LLAMA-JSON-data-extration:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use minkdank/LLAMA-JSON-data-extration with Docker Model Runner:
docker model run hf.co/minkdank/LLAMA-JSON-data-extration:Q4_K_M
- Lemonade
How to use minkdank/LLAMA-JSON-data-extration with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull minkdank/LLAMA-JSON-data-extration:Q4_K_M
Run and chat with the model
lemonade run user.LLAMA-JSON-data-extration-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Trained with Unsloth - config
Browse files- config.json +1 -1
config.json
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 128000,
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"eos_token_id":
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 3072,
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 128000,
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"eos_token_id": 128001,
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 3072,
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