Instructions to use EnlistedGhost/Mistral-7B-Base-v0.3-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use EnlistedGhost/Mistral-7B-Base-v0.3-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="EnlistedGhost/Mistral-7B-Base-v0.3-GGUF", filename="Mistral-7B-Base-v0.3-BF16.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use EnlistedGhost/Mistral-7B-Base-v0.3-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf EnlistedGhost/Mistral-7B-Base-v0.3-GGUF:Q4_K_S # Run inference directly in the terminal: llama-cli -hf EnlistedGhost/Mistral-7B-Base-v0.3-GGUF:Q4_K_S
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf EnlistedGhost/Mistral-7B-Base-v0.3-GGUF:Q4_K_S # Run inference directly in the terminal: llama-cli -hf EnlistedGhost/Mistral-7B-Base-v0.3-GGUF:Q4_K_S
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 EnlistedGhost/Mistral-7B-Base-v0.3-GGUF:Q4_K_S # Run inference directly in the terminal: ./llama-cli -hf EnlistedGhost/Mistral-7B-Base-v0.3-GGUF:Q4_K_S
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 EnlistedGhost/Mistral-7B-Base-v0.3-GGUF:Q4_K_S # Run inference directly in the terminal: ./build/bin/llama-cli -hf EnlistedGhost/Mistral-7B-Base-v0.3-GGUF:Q4_K_S
Use Docker
docker model run hf.co/EnlistedGhost/Mistral-7B-Base-v0.3-GGUF:Q4_K_S
- LM Studio
- Jan
- vLLM
How to use EnlistedGhost/Mistral-7B-Base-v0.3-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "EnlistedGhost/Mistral-7B-Base-v0.3-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "EnlistedGhost/Mistral-7B-Base-v0.3-GGUF", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/EnlistedGhost/Mistral-7B-Base-v0.3-GGUF:Q4_K_S
- Ollama
How to use EnlistedGhost/Mistral-7B-Base-v0.3-GGUF with Ollama:
ollama run hf.co/EnlistedGhost/Mistral-7B-Base-v0.3-GGUF:Q4_K_S
- Unsloth Studio
How to use EnlistedGhost/Mistral-7B-Base-v0.3-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 EnlistedGhost/Mistral-7B-Base-v0.3-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 EnlistedGhost/Mistral-7B-Base-v0.3-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for EnlistedGhost/Mistral-7B-Base-v0.3-GGUF to start chatting
- Docker Model Runner
How to use EnlistedGhost/Mistral-7B-Base-v0.3-GGUF with Docker Model Runner:
docker model run hf.co/EnlistedGhost/Mistral-7B-Base-v0.3-GGUF:Q4_K_S
- Lemonade
How to use EnlistedGhost/Mistral-7B-Base-v0.3-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull EnlistedGhost/Mistral-7B-Base-v0.3-GGUF:Q4_K_S
Run and chat with the model
lemonade run user.Mistral-7B-Base-v0.3-GGUF-Q4_K_S
List all available models
lemonade list
------------------------------------------------
- Model Details and Specifications: -
------------------------------------------------
This release contains:
Llama.cpp and Ollama compatible GGUF converted and Quantized model files
(Compatible with both Ollama, and Llama.cpp)
Quantized GGUF version of:
- mistralai/Mistral-7B-v0.3
(by MistralAI)
Original Model Link:
Citation (Original Paper)
-------------------------------------------------------------
- GGUF Conversion and Quantization Details: -
-------------------------------------------------------------
Software used to convert Safetensors to GGUF:
Software used to create Quantized GGUF Files:
Specific GitHub Commit Point:
Converted to GGUF and Quantized by:
--------------------------
---- Original Info ----
--------------------------
(Crossposted from the link in the above section: "Model Details"):
Model Card for Mistral-7B-v0.3
The Mistral-7B-v0.3 Large Language Model (LLM) is a Mistral-7B-v0.2 with extended vocabulary.
Mistral-7B-v0.3 has the following changes compared to Mistral-7B-v0.2
- Extended vocabulary to 32768
Limitations
The Mistral 7B Instruct model is a quick demonstration that the base model can be easily fine-tuned to achieve compelling performance. It does not have any moderation mechanisms. We're looking forward to engaging with the community on ways to make the model finely respect guardrails, allowing for deployment in environments requiring moderated outputs.
The Mistral AI Team
Albert Jiang, Alexandre Sablayrolles, Alexis Tacnet, Antoine Roux, Arthur Mensch, Audrey Herblin-Stoop, Baptiste Bout, Baudouin de Monicault, Blanche Savary, Bam4d, Caroline Feldman, Devendra Singh Chaplot, Diego de las Casas, Eleonore Arcelin, Emma Bou Hanna, Etienne Metzger, Gianna Lengyel, Guillaume Bour, Guillaume Lample, Harizo Rajaona, Jean-Malo Delignon, Jia Li, Justus Murke, Louis Martin, Louis Ternon, Lucile Saulnier, Lélio Renard Lavaud, Margaret Jennings, Marie Pellat, Marie Torelli, Marie-Anne Lachaux, Nicolas Schuhl, Patrick von Platen, Pierre Stock, Sandeep Subramanian, Sophia Yang, Szymon Antoniak, Teven Le Scao, Thibaut Lavril, Timothée Lacroix, Théophile Gervet, Thomas Wang, Valera Nemychnikova, William El Sayed, William Marshall
- Downloads last month
- 42
2-bit
3-bit
4-bit
5-bit
6-bit
8-bit
16-bit
Model tree for EnlistedGhost/Mistral-7B-Base-v0.3-GGUF
Base model
mistralai/Mistral-7B-v0.3