Instructions to use llmware/slim-tags-3b-tool with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use llmware/slim-tags-3b-tool with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("llmware/slim-tags-3b-tool", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use llmware/slim-tags-3b-tool 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 llmware/slim-tags-3b-tool # Run inference directly in the terminal: llama cli -hf llmware/slim-tags-3b-tool
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf llmware/slim-tags-3b-tool # Run inference directly in the terminal: llama cli -hf llmware/slim-tags-3b-tool
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 llmware/slim-tags-3b-tool # Run inference directly in the terminal: ./llama-cli -hf llmware/slim-tags-3b-tool
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 llmware/slim-tags-3b-tool # Run inference directly in the terminal: ./build/bin/llama-cli -hf llmware/slim-tags-3b-tool
Use Docker
docker model run hf.co/llmware/slim-tags-3b-tool
- LM Studio
- Jan
- Ollama
How to use llmware/slim-tags-3b-tool with Ollama:
ollama run hf.co/llmware/slim-tags-3b-tool
- Unsloth Desktop
- Docker Model Runner
How to use llmware/slim-tags-3b-tool with Docker Model Runner:
docker model run hf.co/llmware/slim-tags-3b-tool
- Lemonade
How to use llmware/slim-tags-3b-tool with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull llmware/slim-tags-3b-tool
Run and chat with the model
lemonade run user.slim-tags-3b-tool-{{QUANT_TAG}}List all available models
lemonade list
- Atomic Chat
Update config.json
Browse files- config.json +7 -19
config.json
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{
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"model_name": "slim-
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"model_ft_base": "slim-
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"quantization": "4Q_K_M GGUF",
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"model_base": "stabilityai/stablelm-3b-4e1t",
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"model_type": "stablelm",
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"tokenizer": "llmware/slim-
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"parameters": "2.7 billion",
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"description": "slim-
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"prompt_wrapper": "human_bot",
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"prompt_format": "<human> {context_passage} <classify>
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"output_format": "{'sentiment': [], 'people': [], 'place': [], 'organization': [], 'misc':[]}",
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"primary_keys": [
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"people",
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"place",
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"organization",
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"misc"
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],
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"output_values": [
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"sentiment",
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"people",
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"place",
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"organization",
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"misc"
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],
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"publisher": "llmware",
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"release_date": "march 2024",
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"test_set": [
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{
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"model_name": "slim-tags-3b-tool",
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"model_ft_base": "slim-tags-3b",
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"quantization": "4Q_K_M GGUF",
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"model_base": "stabilityai/stablelm-3b-4e1t",
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"model_type": "stablelm",
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"tokenizer": "llmware/slim-tags-3b",
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"parameters": "2.7 billion",
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"description": "slim-tags-3b is a function-calling model, fine-tuned to output structured dictionaries",
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"prompt_wrapper": "human_bot",
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"prompt_format": "<human> {context_passage} <classify> tags </classify>\n<bot>:",
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"output_format": "{'sentiment': [], 'people': [], 'place': [], 'organization': [], 'misc':[]}",
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"primary_keys": ["tags"],
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"output_values": ["key_object1", "key_object2", "key_object3", ...],
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"publisher": "llmware",
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"release_date": "march 2024",
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"test_set": [
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