Instructions to use CultriX/Llama3-8B-function-calling-uncensored-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use CultriX/Llama3-8B-function-calling-uncensored-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("CultriX/Llama3-8B-function-calling-uncensored-GGUF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use CultriX/Llama3-8B-function-calling-uncensored-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 CultriX/Llama3-8B-function-calling-uncensored-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf CultriX/Llama3-8B-function-calling-uncensored-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf CultriX/Llama3-8B-function-calling-uncensored-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf CultriX/Llama3-8B-function-calling-uncensored-GGUF:Q4_K_M

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 CultriX/Llama3-8B-function-calling-uncensored-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf CultriX/Llama3-8B-function-calling-uncensored-GGUF:Q4_K_M

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 CultriX/Llama3-8B-function-calling-uncensored-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf CultriX/Llama3-8B-function-calling-uncensored-GGUF:Q4_K_M

Use Docker

docker model run hf.co/CultriX/Llama3-8B-function-calling-uncensored-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use CultriX/Llama3-8B-function-calling-uncensored-GGUF with Ollama:
```
ollama run hf.co/CultriX/Llama3-8B-function-calling-uncensored-GGUF:Q4_K_M
```

Unsloth Studio

How to use CultriX/Llama3-8B-function-calling-uncensored-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 CultriX/Llama3-8B-function-calling-uncensored-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 CultriX/Llama3-8B-function-calling-uncensored-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for CultriX/Llama3-8B-function-calling-uncensored-GGUF to start chatting

Docker Model Runner
How to use CultriX/Llama3-8B-function-calling-uncensored-GGUF with Docker Model Runner:
```
docker model run hf.co/CultriX/Llama3-8B-function-calling-uncensored-GGUF:Q4_K_M
```

Lemonade

How to use CultriX/Llama3-8B-function-calling-uncensored-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull CultriX/Llama3-8B-function-calling-uncensored-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Llama3-8B-function-calling-uncensored-GGUF-Q4_K_M

List all available models

lemonade list

Atomic Chat

merge

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

Merge Details

Merge Method

This model was merged using the task arithmetic merge method using UCLA-AGI/Llama-3-Instruct-8B-SPPO-Iter3 as a base.

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

slices:
  - sources:
      - model: hiieu/Meta-Llama-3-8B-Instruct-function-calling-json-mode
        parameters:
          weight: 1
        layer_range: [0, 32]
      - model: Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2
        parameters:
          weight: 1
        layer_range: [0, 32]
      - model: CultriX/Llama3-8B-DPO
        parameters:
          weight: 0.3
        layer_range: [0, 32]
      - model: UCLA-AGI/Llama-3-Instruct-8B-SPPO-Iter3
        parameters:
          weight: 0.7
        layer_range: [0, 32]
merge_method: task_arithmetic
base_model: UCLA-AGI/Llama-3-Instruct-8B-SPPO-Iter3
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5
dtype: bfloat16

Downloads last month: 37

GGUF

Model size

8B params

Architecture

llama

Hardware compatibility

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

16-bit

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Model tree for CultriX/Llama3-8B-function-calling-uncensored-GGUF

Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2

UCLA-AGI/Llama-3-Instruct-8B-SPPO-Iter3

hiieu/Meta-Llama-3-8B-Instruct-function-calling-json-mode

Merge model

this model

Paper for CultriX/Llama3-8B-function-calling-uncensored-GGUF

Editing Models with Task Arithmetic

Paper • 2212.04089 • Published Dec 8, 2022 • 9