Instructions to use jfiekdjdk/Human-Like-Qwen2.5-7B-Instruct-Q4_K_M-GGUF 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 jfiekdjdk/Human-Like-Qwen2.5-7B-Instruct-Q4_K_M-GGUF 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 jfiekdjdk/Human-Like-Qwen2.5-7B-Instruct-Q4_K_M-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf jfiekdjdk/Human-Like-Qwen2.5-7B-Instruct-Q4_K_M-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf jfiekdjdk/Human-Like-Qwen2.5-7B-Instruct-Q4_K_M-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf jfiekdjdk/Human-Like-Qwen2.5-7B-Instruct-Q4_K_M-GGUF:Q4_K_M
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 jfiekdjdk/Human-Like-Qwen2.5-7B-Instruct-Q4_K_M-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf jfiekdjdk/Human-Like-Qwen2.5-7B-Instruct-Q4_K_M-GGUF:Q4_K_M
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 jfiekdjdk/Human-Like-Qwen2.5-7B-Instruct-Q4_K_M-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf jfiekdjdk/Human-Like-Qwen2.5-7B-Instruct-Q4_K_M-GGUF:Q4_K_M
Use Docker
docker model run hf.co/jfiekdjdk/Human-Like-Qwen2.5-7B-Instruct-Q4_K_M-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use jfiekdjdk/Human-Like-Qwen2.5-7B-Instruct-Q4_K_M-GGUF with Ollama:
ollama run hf.co/jfiekdjdk/Human-Like-Qwen2.5-7B-Instruct-Q4_K_M-GGUF:Q4_K_M
- Unsloth Studio
How to use jfiekdjdk/Human-Like-Qwen2.5-7B-Instruct-Q4_K_M-GGUF with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for jfiekdjdk/Human-Like-Qwen2.5-7B-Instruct-Q4_K_M-GGUF to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for jfiekdjdk/Human-Like-Qwen2.5-7B-Instruct-Q4_K_M-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for jfiekdjdk/Human-Like-Qwen2.5-7B-Instruct-Q4_K_M-GGUF to start chatting
- Docker Model Runner
How to use jfiekdjdk/Human-Like-Qwen2.5-7B-Instruct-Q4_K_M-GGUF with Docker Model Runner:
docker model run hf.co/jfiekdjdk/Human-Like-Qwen2.5-7B-Instruct-Q4_K_M-GGUF:Q4_K_M
- Lemonade
How to use jfiekdjdk/Human-Like-Qwen2.5-7B-Instruct-Q4_K_M-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull jfiekdjdk/Human-Like-Qwen2.5-7B-Instruct-Q4_K_M-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Human-Like-Qwen2.5-7B-Instruct-Q4_K_M-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
jfiekdjdk/Human-Like-Qwen2.5-7B-Instruct-Q4_K_M-GGUF
This model was converted to GGUF format from HumanLLMs/Human-Like-Qwen2.5-7B-Instruct using llama.cpp via the ggml.ai's GGUF-my-repo space.
Refer to the original model card for more details on the model.
Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)
brew install llama.cpp
Invoke the llama.cpp server or the CLI.
CLI:
llama-cli --hf-repo jfiekdjdk/Human-Like-Qwen2.5-7B-Instruct-Q4_K_M-GGUF --hf-file human-like-qwen2.5-7b-instruct-q4_k_m.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo jfiekdjdk/Human-Like-Qwen2.5-7B-Instruct-Q4_K_M-GGUF --hf-file human-like-qwen2.5-7b-instruct-q4_k_m.gguf -c 2048
Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.
Step 1: Clone llama.cpp from GitHub.
git clone https://github.com/ggerganov/llama.cpp
Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1 flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
cd llama.cpp && LLAMA_CURL=1 make
Step 3: Run inference through the main binary.
./llama-cli --hf-repo jfiekdjdk/Human-Like-Qwen2.5-7B-Instruct-Q4_K_M-GGUF --hf-file human-like-qwen2.5-7b-instruct-q4_k_m.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo jfiekdjdk/Human-Like-Qwen2.5-7B-Instruct-Q4_K_M-GGUF --hf-file human-like-qwen2.5-7b-instruct-q4_k_m.gguf -c 2048
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Model tree for jfiekdjdk/Human-Like-Qwen2.5-7B-Instruct-Q4_K_M-GGUF
Base model
Qwen/Qwen2.5-7BEvaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard72.840
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard34.480
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard0.000
- acc_norm on GPQA (0-shot)Open LLM Leaderboard6.490
- acc_norm on MuSR (0-shot)Open LLM Leaderboard8.420
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard37.760
docker model run hf.co/jfiekdjdk/Human-Like-Qwen2.5-7B-Instruct-Q4_K_M-GGUF:Q4_K_M