Instructions to use steef68/ATLAS-QUANTUM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use steef68/ATLAS-QUANTUM with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="steef68/ATLAS-QUANTUM",
	filename="ATLAS-QUANTUM-7B-Uncensored.q2_K.gguf",
)

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

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use steef68/ATLAS-QUANTUM with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf steef68/ATLAS-QUANTUM:Q2_K
# Run inference directly in the terminal:
llama-cli -hf steef68/ATLAS-QUANTUM:Q2_K

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf steef68/ATLAS-QUANTUM:Q2_K
# Run inference directly in the terminal:
llama-cli -hf steef68/ATLAS-QUANTUM: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 steef68/ATLAS-QUANTUM:Q2_K
# Run inference directly in the terminal:
./llama-cli -hf steef68/ATLAS-QUANTUM: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 steef68/ATLAS-QUANTUM:Q2_K
# Run inference directly in the terminal:
./build/bin/llama-cli -hf steef68/ATLAS-QUANTUM:Q2_K

Use Docker

docker model run hf.co/steef68/ATLAS-QUANTUM:Q2_K

LM Studio
Jan
Ollama
How to use steef68/ATLAS-QUANTUM with Ollama:
```
ollama run hf.co/steef68/ATLAS-QUANTUM:Q2_K
```

Unsloth Studio new

How to use steef68/ATLAS-QUANTUM 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 steef68/ATLAS-QUANTUM 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 steef68/ATLAS-QUANTUM to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for steef68/ATLAS-QUANTUM to start chatting

Docker Model Runner
How to use steef68/ATLAS-QUANTUM with Docker Model Runner:
```
docker model run hf.co/steef68/ATLAS-QUANTUM:Q2_K
```

Lemonade

How to use steef68/ATLAS-QUANTUM with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull steef68/ATLAS-QUANTUM:Q2_K

Run and chat with the model

lemonade run user.ATLAS-QUANTUM-Q2_K

List all available models

lemonade list

Update README.md

by derricka59 - opened Nov 30, 2024

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Explanation of Additions:

Metadata Block: Includes essential details such as library_name, tags, datasets, model_architecture, and other relevant fields to align with Hugging Face's model card standards.
Model Details: Expands on model usage, applications, and limitations.
Resources and Licensing: Provides clear references for further support and licensing information.
Placeholders: Marked where dataset details are missing for future updates.

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