Instructions to use netcat420/MFANN3bv0.7.10-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use netcat420/MFANN3bv0.7.10-GGUF with Adapters:

from adapters import AutoAdapterModel

model = AutoAdapterModel.from_pretrained("undefined")
model.load_adapter("netcat420/MFANN3bv0.7.10-GGUF", set_active=True)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use netcat420/MFANN3bv0.7.10-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 netcat420/MFANN3bv0.7.10-GGUF
# Run inference directly in the terminal:
llama cli -hf netcat420/MFANN3bv0.7.10-GGUF

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf netcat420/MFANN3bv0.7.10-GGUF
# Run inference directly in the terminal:
llama cli -hf netcat420/MFANN3bv0.7.10-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 netcat420/MFANN3bv0.7.10-GGUF
# Run inference directly in the terminal:
./llama-cli -hf netcat420/MFANN3bv0.7.10-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 netcat420/MFANN3bv0.7.10-GGUF
# Run inference directly in the terminal:
./build/bin/llama-cli -hf netcat420/MFANN3bv0.7.10-GGUF

Use Docker

docker model run hf.co/netcat420/MFANN3bv0.7.10-GGUF

LM Studio
Jan
Ollama
How to use netcat420/MFANN3bv0.7.10-GGUF with Ollama:
```
ollama run hf.co/netcat420/MFANN3bv0.7.10-GGUF
```

Unsloth Studio

How to use netcat420/MFANN3bv0.7.10-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 netcat420/MFANN3bv0.7.10-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 netcat420/MFANN3bv0.7.10-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for netcat420/MFANN3bv0.7.10-GGUF to start chatting

Atomic Chat new
Docker Model Runner
How to use netcat420/MFANN3bv0.7.10-GGUF with Docker Model Runner:
```
docker model run hf.co/netcat420/MFANN3bv0.7.10-GGUF
```

Lemonade

How to use netcat420/MFANN3bv0.7.10-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull netcat420/MFANN3bv0.7.10-GGUF

Run and chat with the model

lemonade run user.MFANN3bv0.7.10-GGUF-{{QUANT_TAG}}

List all available models

lemonade list

base_model: - netcat420/MFANN3bv0.3 - netcat420/MFANN3bv0.7 - liminerity/Phigments12 - netcat420/MFANN3bv0.6 library_name: transformers tags: - mergekit - merge license: apache-2.0

MFANN3bv0.7.10

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

Merge Details

Merge Method

This model was merged using the TIES merge method using liminerity/Phigments12 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: netcat420/MFANN3bv0.6
    parameters:
      density: [1, 0.7, 0.1] # density gradient
      weight: 1.0
  - model: netcat420/MFANN3bv0.3
    parameters:
      density: 0.5
      weight: [0, 0.3, 0.7, 1] # weight gradient
  - model: netcat420/MFANN3bv0.7
    parameters:
      density: 0.33
      weight:
        - filter: mlp
          value: 0.5
        - value: 0
merge_method: ties
base_model: liminerity/Phigments12
parameters:
  normalize: true
  int8_mask: true
dtype: float16

System prompt

### System:
### thought-process:

Downloads last month: 17

GGUF

Model size

3B params

Architecture

phi2

Hardware compatibility

We're not able to determine the quantization variants.

View all variants

Paper for netcat420/MFANN3bv0.7.10-GGUF

Resolving Interference When Merging Models

Paper • 2306.01708 • Published Jun 2, 2023 • 19