LLM Nexus: The Future of Language Models
Collection
Top-tier Large Language Models (LLMs) for developers and researchers. Elevate your projects with cutting-edge AI from LLM Nexus. • 5 items • Updated • 2
How to use Diluzx/mistral-7b-v0.3-bnb-4bit with Transformers:
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Diluzx/mistral-7b-v0.3-bnb-4bit", device_map="auto")How to use Diluzx/mistral-7b-v0.3-bnb-4bit with llama.cpp:
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf Diluzx/mistral-7b-v0.3-bnb-4bit:F16 # Run inference directly in the terminal: llama cli -hf Diluzx/mistral-7b-v0.3-bnb-4bit:F16
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Diluzx/mistral-7b-v0.3-bnb-4bit:F16 # Run inference directly in the terminal: llama cli -hf Diluzx/mistral-7b-v0.3-bnb-4bit:F16
# 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 Diluzx/mistral-7b-v0.3-bnb-4bit:F16 # Run inference directly in the terminal: ./llama-cli -hf Diluzx/mistral-7b-v0.3-bnb-4bit:F16
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 Diluzx/mistral-7b-v0.3-bnb-4bit:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf Diluzx/mistral-7b-v0.3-bnb-4bit:F16
docker model run hf.co/Diluzx/mistral-7b-v0.3-bnb-4bit:F16
How to use Diluzx/mistral-7b-v0.3-bnb-4bit with Ollama:
ollama run hf.co/Diluzx/mistral-7b-v0.3-bnb-4bit:F16
How to use Diluzx/mistral-7b-v0.3-bnb-4bit with Docker Model Runner:
docker model run hf.co/Diluzx/mistral-7b-v0.3-bnb-4bit:F16
How to use Diluzx/mistral-7b-v0.3-bnb-4bit with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Diluzx/mistral-7b-v0.3-bnb-4bit:F16
lemonade run user.mistral-7b-v0.3-bnb-4bit-F16
lemonade list
This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.
5-bit
16-bit
Base model
mistralai/Mistral-7B-v0.3
docker model run hf.co/Diluzx/mistral-7b-v0.3-bnb-4bit:F16