Instructions to use mradermacher/Llama-3.1-Tango-8b-f16-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use mradermacher/Llama-3.1-Tango-8b-f16-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("mradermacher/Llama-3.1-Tango-8b-f16-GGUF", dtype="auto")

llama-cpp-python

How to use mradermacher/Llama-3.1-Tango-8b-f16-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="mradermacher/Llama-3.1-Tango-8b-f16-GGUF",
	filename="Llama-3.1-Tango-8b-f16.IQ4_XS.gguf",
)

output = llm(
	"Once upon a time,",
	max_tokens=512,
	echo=True
)
print(output)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use mradermacher/Llama-3.1-Tango-8b-f16-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 mradermacher/Llama-3.1-Tango-8b-f16-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf mradermacher/Llama-3.1-Tango-8b-f16-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 mradermacher/Llama-3.1-Tango-8b-f16-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf mradermacher/Llama-3.1-Tango-8b-f16-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-3.1-Tango-8b-f16-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf mradermacher/Llama-3.1-Tango-8b-f16-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-3.1-Tango-8b-f16-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf mradermacher/Llama-3.1-Tango-8b-f16-GGUF:Q4_K_M

Use Docker

docker model run hf.co/mradermacher/Llama-3.1-Tango-8b-f16-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use mradermacher/Llama-3.1-Tango-8b-f16-GGUF with Ollama:
```
ollama run hf.co/mradermacher/Llama-3.1-Tango-8b-f16-GGUF:Q4_K_M
```

Unsloth Studio

How to use mradermacher/Llama-3.1-Tango-8b-f16-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-3.1-Tango-8b-f16-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-3.1-Tango-8b-f16-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-3.1-Tango-8b-f16-GGUF to start chatting

Atomic Chat new
Docker Model Runner
How to use mradermacher/Llama-3.1-Tango-8b-f16-GGUF with Docker Model Runner:
```
docker model run hf.co/mradermacher/Llama-3.1-Tango-8b-f16-GGUF:Q4_K_M
```

Lemonade

How to use mradermacher/Llama-3.1-Tango-8b-f16-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull mradermacher/Llama-3.1-Tango-8b-f16-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Llama-3.1-Tango-8b-f16-GGUF-Q4_K_M

List all available models

lemonade list

mradermacher commited on Dec 8, 2024

Commit

79444b7

verified ·

1 Parent(s): 27db394

auto-patch README.md

Browse files

Files changed (1) hide show

README.md +3 -1

README.md CHANGED Viewed

@@ -28,7 +28,7 @@ tags:
 static quants of https://huggingface.co/sandbox-ai/Llama-3.1-Tango-8b-f16
 <!-- provided-files -->
-weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
 ## Usage
 If you are unsure how to use GGUF files, refer to one of [TheBloke's
@@ -45,6 +45,8 @@ more details, including on how to concatenate multi-part files.
 | [GGUF](https://huggingface.co/mradermacher/Llama-3.1-Tango-8b-f16-GGUF/resolve/main/Llama-3.1-Tango-8b-f16.Q3_K_S.gguf) | Q3_K_S | 3.8 |  |
 | [GGUF](https://huggingface.co/mradermacher/Llama-3.1-Tango-8b-f16-GGUF/resolve/main/Llama-3.1-Tango-8b-f16.Q3_K_M.gguf) | Q3_K_M | 4.1 | lower quality |
 | [GGUF](https://huggingface.co/mradermacher/Llama-3.1-Tango-8b-f16-GGUF/resolve/main/Llama-3.1-Tango-8b-f16.Q3_K_L.gguf) | Q3_K_L | 4.4 |  |
 | [GGUF](https://huggingface.co/mradermacher/Llama-3.1-Tango-8b-f16-GGUF/resolve/main/Llama-3.1-Tango-8b-f16.Q4_K_S.gguf) | Q4_K_S | 4.8 | fast, recommended |
 | [GGUF](https://huggingface.co/mradermacher/Llama-3.1-Tango-8b-f16-GGUF/resolve/main/Llama-3.1-Tango-8b-f16.Q4_K_M.gguf) | Q4_K_M | 5.0 | fast, recommended |
 | [GGUF](https://huggingface.co/mradermacher/Llama-3.1-Tango-8b-f16-GGUF/resolve/main/Llama-3.1-Tango-8b-f16.Q5_K_S.gguf) | Q5_K_S | 5.7 |  |

 static quants of https://huggingface.co/sandbox-ai/Llama-3.1-Tango-8b-f16
 <!-- provided-files -->
+weighted/imatrix quants are available at https://huggingface.co/mradermacher/Llama-3.1-Tango-8b-f16-i1-GGUF
 ## Usage
 If you are unsure how to use GGUF files, refer to one of [TheBloke's
 | [GGUF](https://huggingface.co/mradermacher/Llama-3.1-Tango-8b-f16-GGUF/resolve/main/Llama-3.1-Tango-8b-f16.Q3_K_S.gguf) | Q3_K_S | 3.8 |  |
 | [GGUF](https://huggingface.co/mradermacher/Llama-3.1-Tango-8b-f16-GGUF/resolve/main/Llama-3.1-Tango-8b-f16.Q3_K_M.gguf) | Q3_K_M | 4.1 | lower quality |
 | [GGUF](https://huggingface.co/mradermacher/Llama-3.1-Tango-8b-f16-GGUF/resolve/main/Llama-3.1-Tango-8b-f16.Q3_K_L.gguf) | Q3_K_L | 4.4 |  |
+| [GGUF](https://huggingface.co/mradermacher/Llama-3.1-Tango-8b-f16-GGUF/resolve/main/Llama-3.1-Tango-8b-f16.IQ4_XS.gguf) | IQ4_XS | 4.6 |  |
+| [GGUF](https://huggingface.co/mradermacher/Llama-3.1-Tango-8b-f16-GGUF/resolve/main/Llama-3.1-Tango-8b-f16.Q4_0_4_4.gguf) | Q4_0_4_4 | 4.8 | fast on arm, low quality |
 | [GGUF](https://huggingface.co/mradermacher/Llama-3.1-Tango-8b-f16-GGUF/resolve/main/Llama-3.1-Tango-8b-f16.Q4_K_S.gguf) | Q4_K_S | 4.8 | fast, recommended |
 | [GGUF](https://huggingface.co/mradermacher/Llama-3.1-Tango-8b-f16-GGUF/resolve/main/Llama-3.1-Tango-8b-f16.Q4_K_M.gguf) | Q4_K_M | 5.0 | fast, recommended |
 | [GGUF](https://huggingface.co/mradermacher/Llama-3.1-Tango-8b-f16-GGUF/resolve/main/Llama-3.1-Tango-8b-f16.Q5_K_S.gguf) | Q5_K_S | 5.7 |  |