Instructions to use tensorblock/tiny-random-Llama-3-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use tensorblock/tiny-random-Llama-3-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("tensorblock/tiny-random-Llama-3-GGUF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use tensorblock/tiny-random-Llama-3-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 tensorblock/tiny-random-Llama-3-GGUF:Q2_K
# Run inference directly in the terminal:
llama cli -hf tensorblock/tiny-random-Llama-3-GGUF:Q2_K

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf tensorblock/tiny-random-Llama-3-GGUF:Q2_K
# Run inference directly in the terminal:
llama cli -hf tensorblock/tiny-random-Llama-3-GGUF:Q2_K

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 tensorblock/tiny-random-Llama-3-GGUF:Q2_K
# Run inference directly in the terminal:
./llama-cli -hf tensorblock/tiny-random-Llama-3-GGUF:Q2_K

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 tensorblock/tiny-random-Llama-3-GGUF:Q2_K
# Run inference directly in the terminal:
./build/bin/llama-cli -hf tensorblock/tiny-random-Llama-3-GGUF:Q2_K

Use Docker

docker model run hf.co/tensorblock/tiny-random-Llama-3-GGUF:Q2_K

LM Studio
Jan
Ollama
How to use tensorblock/tiny-random-Llama-3-GGUF with Ollama:
```
ollama run hf.co/tensorblock/tiny-random-Llama-3-GGUF:Q2_K
```
Unsloth Desktop
Docker Model Runner
How to use tensorblock/tiny-random-Llama-3-GGUF with Docker Model Runner:
```
docker model run hf.co/tensorblock/tiny-random-Llama-3-GGUF:Q2_K
```

Lemonade

How to use tensorblock/tiny-random-Llama-3-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull tensorblock/tiny-random-Llama-3-GGUF:Q2_K

Run and chat with the model

lemonade run user.tiny-random-Llama-3-GGUF-Q2_K

List all available models

lemonade list

Atomic Chat

tiny-random-Llama-3-GGUF / tiny-random-Llama-3-Q2_K.gguf

morriszms

Upload folder using huggingface_hub

39f9d02 verified almost 2 years ago

History Blame GGUF Editor new Delete

14.1 MB

This file is stored with Xet . It is too big to display, but you can still download it.

Xet Pointer Details

( Raw pointer file )

Xet hash:: 8cae7f0a977cfa56a88d6c6825536346b62f7f2a72bf13d1ad4ad56c836977c5
Size of remote file:: 14.1 MB
SHA256:: 56447375eaf9b972706d7d4712021b0528d1ea265f43e210f21ca96c2a8dfe9d

Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.