Instructions to use second-state/moxin-instruct-7b-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use second-state/moxin-instruct-7b-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="second-state/moxin-instruct-7b-GGUF", filename="moxin-instruct-7b-Q2_K.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use second-state/moxin-instruct-7b-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf second-state/moxin-instruct-7b-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf second-state/moxin-instruct-7b-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf second-state/moxin-instruct-7b-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf second-state/moxin-instruct-7b-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 second-state/moxin-instruct-7b-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf second-state/moxin-instruct-7b-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 second-state/moxin-instruct-7b-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf second-state/moxin-instruct-7b-GGUF:Q4_K_M
Use Docker
docker model run hf.co/second-state/moxin-instruct-7b-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use second-state/moxin-instruct-7b-GGUF with Ollama:
ollama run hf.co/second-state/moxin-instruct-7b-GGUF:Q4_K_M
- Unsloth Studio
How to use second-state/moxin-instruct-7b-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 second-state/moxin-instruct-7b-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 second-state/moxin-instruct-7b-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for second-state/moxin-instruct-7b-GGUF to start chatting
- Docker Model Runner
How to use second-state/moxin-instruct-7b-GGUF with Docker Model Runner:
docker model run hf.co/second-state/moxin-instruct-7b-GGUF:Q4_K_M
- Lemonade
How to use second-state/moxin-instruct-7b-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull second-state/moxin-instruct-7b-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.moxin-instruct-7b-GGUF-Q4_K_M
List all available models
lemonade list
| { | |
| "_name_or_path": "/shared/user93/workspace/open-instruct/output/sft_8b_11k5_final/", | |
| "architectures": [ | |
| "MistralForCausalLM" | |
| ], | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 1, | |
| "eos_token_id": 2, | |
| "head_dim": 128, | |
| "hidden_act": "silu", | |
| "hidden_size": 4096, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 14336, | |
| "max_position_embeddings": 32768, | |
| "model_type": "mistral", | |
| "num_attention_heads": 32, | |
| "num_hidden_layers": 36, | |
| "num_key_value_heads": 8, | |
| "rms_norm_eps": 1e-05, | |
| "rope_theta": 10000.0, | |
| "sliding_window": 4096, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "bfloat16", | |
| "transformers_version": "4.43.4", | |
| "use_cache": true, | |
| "vocab_size": 32008 | |
| } | |