GGUF
mergekit
Merge
How to use from
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 saishf/Top-Western-Maid-7B-GGUF:
# Run inference directly in the terminal:
llama cli -hf saishf/Top-Western-Maid-7B-GGUF:
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf saishf/Top-Western-Maid-7B-GGUF:
# Run inference directly in the terminal:
llama cli -hf saishf/Top-Western-Maid-7B-GGUF:
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 saishf/Top-Western-Maid-7B-GGUF:
# Run inference directly in the terminal:
./llama-cli -hf saishf/Top-Western-Maid-7B-GGUF:
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 saishf/Top-Western-Maid-7B-GGUF:
# Run inference directly in the terminal:
./build/bin/llama-cli -hf saishf/Top-Western-Maid-7B-GGUF:
Use Docker
docker model run hf.co/saishf/Top-Western-Maid-7B-GGUF:
Quick Links

merge

This is a merge of pre-trained language models created using mergekit.

Merge Details

Merge Method

This model was merged using the DARE TIES merge method using mistralai/Mistral-7B-v0.1 as a base.

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: mistralai/Mistral-7B-v0.1
    # No parameters necessary for base model
  - model: senseable/WestLake-7B-v2
    parameters:
      density: 0.53
      weight: 0.55
  - model: NeverSleep/Noromaid-7B-0.4-DPO
    parameters:
      density: 0.53
      weight: 0.30  
  - model: Undi95/Toppy-M-7B
    parameters:
      density: 0.53
      weight: 0.15  
merge_method: dare_ties
base_model: mistralai/Mistral-7B-v0.1
parameters:
  int8_mask: true
dtype: bfloat16
Downloads last month
51
GGUF
Model size
7B params
Architecture
llama
Hardware compatibility
Log In to add your hardware

2-bit

3-bit

4-bit

5-bit

6-bit

Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for saishf/Top-Western-Maid-7B-GGUF

Papers for saishf/Top-Western-Maid-7B-GGUF