Instructions to use mradermacher/LLAMA-3_8B_Unaligned_BETA-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use mradermacher/LLAMA-3_8B_Unaligned_BETA-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("mradermacher/LLAMA-3_8B_Unaligned_BETA-GGUF", dtype="auto")

llama-cpp-python

How to use mradermacher/LLAMA-3_8B_Unaligned_BETA-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="mradermacher/LLAMA-3_8B_Unaligned_BETA-GGUF",
	filename="LLAMA-3_8B_Unaligned_BETA.IQ4_XS.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use mradermacher/LLAMA-3_8B_Unaligned_BETA-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf mradermacher/LLAMA-3_8B_Unaligned_BETA-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf mradermacher/LLAMA-3_8B_Unaligned_BETA-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf mradermacher/LLAMA-3_8B_Unaligned_BETA-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf mradermacher/LLAMA-3_8B_Unaligned_BETA-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 mradermacher/LLAMA-3_8B_Unaligned_BETA-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf mradermacher/LLAMA-3_8B_Unaligned_BETA-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 mradermacher/LLAMA-3_8B_Unaligned_BETA-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf mradermacher/LLAMA-3_8B_Unaligned_BETA-GGUF:Q4_K_M

Use Docker

docker model run hf.co/mradermacher/LLAMA-3_8B_Unaligned_BETA-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use mradermacher/LLAMA-3_8B_Unaligned_BETA-GGUF with Ollama:
```
ollama run hf.co/mradermacher/LLAMA-3_8B_Unaligned_BETA-GGUF:Q4_K_M
```

Unsloth Studio new

How to use mradermacher/LLAMA-3_8B_Unaligned_BETA-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 mradermacher/LLAMA-3_8B_Unaligned_BETA-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 mradermacher/LLAMA-3_8B_Unaligned_BETA-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for mradermacher/LLAMA-3_8B_Unaligned_BETA-GGUF to start chatting

Docker Model Runner
How to use mradermacher/LLAMA-3_8B_Unaligned_BETA-GGUF with Docker Model Runner:
```
docker model run hf.co/mradermacher/LLAMA-3_8B_Unaligned_BETA-GGUF:Q4_K_M
```

Lemonade

How to use mradermacher/LLAMA-3_8B_Unaligned_BETA-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull mradermacher/LLAMA-3_8B_Unaligned_BETA-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.LLAMA-3_8B_Unaligned_BETA-GGUF-Q4_K_M

List all available models

lemonade list

LLAMA-3_8B_Unaligned_BETA-GGUF / README.md

mradermacher

auto-patch README.md

efc4907 verified over 1 year ago

preview code

raw

history blame contribute delete

3.64 kB

	---
	base_model: SicariusSicariiStuff/LLAMA-3_8B_Unaligned_BETA
	language:
	- en
	library_name: transformers
	license: llama3.1
	quantized_by: mradermacher
	---
	## About

	<!-- ### quantize_version: 2 -->
	<!-- ### output_tensor_quantised: 1 -->
	<!-- ### convert_type: hf -->
	<!-- ### vocab_type: -->
	<!-- ### tags: -->
	static quants of https://huggingface.co/SicariusSicariiStuff/LLAMA-3_8B_Unaligned_BETA

	<!-- provided-files -->
	weighted/imatrix quants are available at https://huggingface.co/mradermacher/LLAMA-3_8B_Unaligned_BETA-i1-GGUF
	## Usage

	If you are unsure how to use GGUF files, refer to one of [TheBloke's
	READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for
	more details, including on how to concatenate multi-part files.

	## Provided Quants

	(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

	\| Link \| Type \| Size/GB \| Notes \|
	\|:-----\|:-----\|--------:\|:------\|
	\| [GGUF](https://huggingface.co/mradermacher/LLAMA-3_8B_Unaligned_BETA-GGUF/resolve/main/LLAMA-3_8B_Unaligned_BETA.Q2_K.gguf) \| Q2_K \| 3.3 \| \|
	\| [GGUF](https://huggingface.co/mradermacher/LLAMA-3_8B_Unaligned_BETA-GGUF/resolve/main/LLAMA-3_8B_Unaligned_BETA.Q3_K_S.gguf) \| Q3_K_S \| 3.8 \| \|
	\| [GGUF](https://huggingface.co/mradermacher/LLAMA-3_8B_Unaligned_BETA-GGUF/resolve/main/LLAMA-3_8B_Unaligned_BETA.Q3_K_M.gguf) \| Q3_K_M \| 4.1 \| lower quality \|
	\| [GGUF](https://huggingface.co/mradermacher/LLAMA-3_8B_Unaligned_BETA-GGUF/resolve/main/LLAMA-3_8B_Unaligned_BETA.Q3_K_L.gguf) \| Q3_K_L \| 4.4 \| \|
	\| [GGUF](https://huggingface.co/mradermacher/LLAMA-3_8B_Unaligned_BETA-GGUF/resolve/main/LLAMA-3_8B_Unaligned_BETA.IQ4_XS.gguf) \| IQ4_XS \| 4.6 \| \|
	\| [GGUF](https://huggingface.co/mradermacher/LLAMA-3_8B_Unaligned_BETA-GGUF/resolve/main/LLAMA-3_8B_Unaligned_BETA.Q4_0_4_4.gguf) \| Q4_0_4_4 \| 4.8 \| fast on arm, low quality \|
	\| [GGUF](https://huggingface.co/mradermacher/LLAMA-3_8B_Unaligned_BETA-GGUF/resolve/main/LLAMA-3_8B_Unaligned_BETA.Q4_K_S.gguf) \| Q4_K_S \| 4.8 \| fast, recommended \|
	\| [GGUF](https://huggingface.co/mradermacher/LLAMA-3_8B_Unaligned_BETA-GGUF/resolve/main/LLAMA-3_8B_Unaligned_BETA.Q4_K_M.gguf) \| Q4_K_M \| 5.0 \| fast, recommended \|
	\| [GGUF](https://huggingface.co/mradermacher/LLAMA-3_8B_Unaligned_BETA-GGUF/resolve/main/LLAMA-3_8B_Unaligned_BETA.Q5_K_S.gguf) \| Q5_K_S \| 5.7 \| \|
	\| [GGUF](https://huggingface.co/mradermacher/LLAMA-3_8B_Unaligned_BETA-GGUF/resolve/main/LLAMA-3_8B_Unaligned_BETA.Q5_K_M.gguf) \| Q5_K_M \| 5.8 \| \|
	\| [GGUF](https://huggingface.co/mradermacher/LLAMA-3_8B_Unaligned_BETA-GGUF/resolve/main/LLAMA-3_8B_Unaligned_BETA.Q6_K.gguf) \| Q6_K \| 6.7 \| very good quality \|
	\| [GGUF](https://huggingface.co/mradermacher/LLAMA-3_8B_Unaligned_BETA-GGUF/resolve/main/LLAMA-3_8B_Unaligned_BETA.Q8_0.gguf) \| Q8_0 \| 8.6 \| fast, best quality \|
	\| [GGUF](https://huggingface.co/mradermacher/LLAMA-3_8B_Unaligned_BETA-GGUF/resolve/main/LLAMA-3_8B_Unaligned_BETA.f16.gguf) \| f16 \| 16.2 \| 16 bpw, overkill \|

	Here is a handy graph by ikawrakow comparing some lower-quality quant
	types (lower is better):

	![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)

	And here are Artefact2's thoughts on the matter:
	https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

	## FAQ / Model Request

	See https://huggingface.co/mradermacher/model_requests for some answers to
	questions you might have and/or if you want some other model quantized.

	## Thanks

	I thank my company, [nethype GmbH](https://www.nethype.de/), for letting
	me use its servers and providing upgrades to my workstation to enable
	this work in my free time.

	<!-- end -->