How to use from
llama.cppInstall from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf PsiPi/ToolBench_ToolLLaMA-2-7b.Q6_K.gguf:Q6_K# Run inference directly in the terminal:
llama cli -hf PsiPi/ToolBench_ToolLLaMA-2-7b.Q6_K.gguf:Q6_KUse 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 PsiPi/ToolBench_ToolLLaMA-2-7b.Q6_K.gguf:Q6_K# Run inference directly in the terminal:
./llama-cli -hf PsiPi/ToolBench_ToolLLaMA-2-7b.Q6_K.gguf:Q6_KBuild 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 PsiPi/ToolBench_ToolLLaMA-2-7b.Q6_K.gguf:Q6_K# Run inference directly in the terminal:
./build/bin/llama-cli -hf PsiPi/ToolBench_ToolLLaMA-2-7b.Q6_K.gguf:Q6_KUse Docker
docker model run hf.co/PsiPi/ToolBench_ToolLLaMA-2-7b.Q6_K.gguf:Q6_KQuick Links
Model Card for Model ID
This is Q6_K gguf quant of ToolLLaMA-2-7b version model introduced in ToolBench.
Original Model Details
ToolBench/ToolLLaMA-2-7b-v2
Model Description
- License: llama2
- Quant: Q6_K
- Format GGUF
- Finetuned from model [optional]: LLaMA-2-7b-hf
Uses
Refer to ToolBench.
Training Details
Trained with the new version data in ToolBench.
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Hardware compatibility
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Install (macOS, Linux)
# Start a local OpenAI-compatible server with a web UI: llama serve -hf PsiPi/ToolBench_ToolLLaMA-2-7b.Q6_K.gguf:Q6_K# Run inference directly in the terminal: llama cli -hf PsiPi/ToolBench_ToolLLaMA-2-7b.Q6_K.gguf:Q6_K