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

base: refs/heads/main

←

from: refs/pr/2

Discussion Files changed

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derricka59

Nov 30, 2024

No description provided.

Update README.md82ad2462

derricka59

Nov 30, 2024

Pull Request: Update README.md with YAML Metadata and Expanded Documentation

Description

This pull request addresses the following issues:

YAML Metadata Warning: The previous README.md lacked the required YAML metadata, causing Hugging Face to raise warnings. This has been resolved by adding a compliant metadata block.
Improved Documentation: Expanded the README to include:

A detailed Overview of the ATLAS-QUANTUM model.

Instructions for Quick Start and model usage.

Additional Resources and guidance for troubleshooting runtime issues.

Updated License details.

Enhanced Usability: Included example code for loading and running the model to improve usability for developers.

Changes Made

YAML Metadata Block: Added the following fields:

library_name: llama

tags: [quantization, efficient-inference, machine-learning, language-model]

license: apache-2.0

datasets: [] (placeholder for actual datasets)

language: en

model_architecture: llama

model_size: 6.74B

quantization: Q2_K

inference: true

Documentation Enhancements:

Clarified the model's architecture, purpose, and supported language.

Provided step-by-step usage instructions.

Linked to resources for further support.

Highlighted known runtime issues.

Testing

Verified that the YAML metadata resolves warnings on Hugging Face.

Checked rendering of the README for formatting and clarity.

Further Action

Replace placeholders like with accurate details when available.

Continue to refine and expand the documentation based on community feedback.

References

ATLAS-QUANTUM Repository

Hugging Face Model Card Metadata Documentation

This description provides a clear and structured overview of the changes made, their purpose, and the next steps.

Upload images, audio, and videos by dragging in the text input, pasting, or clicking here.

Tap or paste here to upload images

Ready to merge

This branch is ready to get merged automatically.

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