Instructions to use alexcovo/dolphin-2.8-mistral-7b-v02-Q4_0-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use alexcovo/dolphin-2.8-mistral-7b-v02-Q4_0-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="alexcovo/dolphin-2.8-mistral-7b-v02-Q4_0-GGUF", filename="dolphin-2.8-mistral-7b-v02.Q4_0.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 alexcovo/dolphin-2.8-mistral-7b-v02-Q4_0-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 alexcovo/dolphin-2.8-mistral-7b-v02-Q4_0-GGUF:Q4_0 # Run inference directly in the terminal: llama cli -hf alexcovo/dolphin-2.8-mistral-7b-v02-Q4_0-GGUF:Q4_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf alexcovo/dolphin-2.8-mistral-7b-v02-Q4_0-GGUF:Q4_0 # Run inference directly in the terminal: llama cli -hf alexcovo/dolphin-2.8-mistral-7b-v02-Q4_0-GGUF:Q4_0
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 alexcovo/dolphin-2.8-mistral-7b-v02-Q4_0-GGUF:Q4_0 # Run inference directly in the terminal: ./llama-cli -hf alexcovo/dolphin-2.8-mistral-7b-v02-Q4_0-GGUF:Q4_0
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 alexcovo/dolphin-2.8-mistral-7b-v02-Q4_0-GGUF:Q4_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf alexcovo/dolphin-2.8-mistral-7b-v02-Q4_0-GGUF:Q4_0
Use Docker
docker model run hf.co/alexcovo/dolphin-2.8-mistral-7b-v02-Q4_0-GGUF:Q4_0
- LM Studio
- Jan
- Ollama
How to use alexcovo/dolphin-2.8-mistral-7b-v02-Q4_0-GGUF with Ollama:
ollama run hf.co/alexcovo/dolphin-2.8-mistral-7b-v02-Q4_0-GGUF:Q4_0
- Unsloth Studio
How to use alexcovo/dolphin-2.8-mistral-7b-v02-Q4_0-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 alexcovo/dolphin-2.8-mistral-7b-v02-Q4_0-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 alexcovo/dolphin-2.8-mistral-7b-v02-Q4_0-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for alexcovo/dolphin-2.8-mistral-7b-v02-Q4_0-GGUF to start chatting
- Atomic Chat new
- Docker Model Runner
How to use alexcovo/dolphin-2.8-mistral-7b-v02-Q4_0-GGUF with Docker Model Runner:
docker model run hf.co/alexcovo/dolphin-2.8-mistral-7b-v02-Q4_0-GGUF:Q4_0
- Lemonade
How to use alexcovo/dolphin-2.8-mistral-7b-v02-Q4_0-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull alexcovo/dolphin-2.8-mistral-7b-v02-Q4_0-GGUF:Q4_0
Run and chat with the model
lemonade run user.dolphin-2.8-mistral-7b-v02-Q4_0-GGUF-Q4_0
List all available models
lemonade list
alexcovo/dolphin-2.8-mistral-7b-v02-Q4_0-GGUF
This model was converted to GGUF format from cognitivecomputations/dolphin-2.8-mistral-7b-v02 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.
brew install ggerganov/ggerganov/llama.cpp
Invoke the llama.cpp server or the CLI.
CLI:
llama-cli --hf-repo alexcovo/dolphin-2.8-mistral-7b-v02-Q4_0-GGUF --model dolphin-2.8-mistral-7b-v02.Q4_0.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo alexcovo/dolphin-2.8-mistral-7b-v02-Q4_0-GGUF --model dolphin-2.8-mistral-7b-v02.Q4_0.gguf -c 2048
Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.
git clone https://github.com/ggerganov/llama.cpp && cd llama.cpp && make && ./main -m dolphin-2.8-mistral-7b-v02.Q4_0.gguf -n 128
- Downloads last month
- 19
4-bit
Model tree for alexcovo/dolphin-2.8-mistral-7b-v02-Q4_0-GGUF
Base model
mistral-community/Mistral-7B-v0.2Datasets used to train alexcovo/dolphin-2.8-mistral-7b-v02-Q4_0-GGUF
m-a-p/Code-Feedback
QuixiAI/dolphin-coder
Evaluation results
- pass@1 on HumanEvalself-reported0.469