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metadata 
library_name: llama
tags:
  - quantization
  - efficient-inference
  - machine-learning
  - language-model
license: apache-2.0
datasets:
  - ATLAS-QUANTUM
language: en
model_architecture: llama
model_size: 6.74B
quantization: Q2_K
inference: true

ATLAS-QUANTUM

Author: steef68
Repository: ATLAS-QUANTUM

Overview

ATLAS-QUANTUM is a lightweight and efficient implementation of a LLaMA-based language model. It is optimized for environments requiring high efficiency and reduced computational overhead through 2-bit quantization (Q2_K). This configuration is ideal for fast inference while maintaining quality in natural language processing tasks.

Key Features

  • Model Size: 6.74 billion parameters
  • Quantization: 2-bit (Q2_K) for compact deployment
  • Architecture: LLaMA
  • Language Support: English
  • Purpose: Inference-ready, suitable for various NLP applications

Usage

To deploy this model or use it in your application, follow the steps below:

Quick Start

  1. Clone the Repository:

    git clone https://huggingface.co/steef68/ATLAS-QUANTUM
cd ATLAS-QUANTUM

  2. Install Dependencies: Install the required libraries. Ensure compatibility with Hugging Face's transformers library.

  3. Load the Model: Use the following Python code snippet to load and run the model:

from transformers import AutoModelForCausalLM, AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained("steef68/ATLAS-QUANTUM") model = AutoModelForCausalLM.from_pretrained("steef68/ATLAS-QUANTUM", quantization=True)

inputs = tokenizer("Your input text here", return_tensors="pt") outputs = model.generate(inputs["input_ids"], max_length=50) print(tokenizer.decode(outputs[0]))

Notes and Limitations

Runtime Issues: The Hugging Face Space linked to this model has reported runtime errors. If you encounter issues, check your setup and log files.

Documentation: The current documentation is under development. Contributions to improve the model card and repository are encouraged.

Resources

Model Repository: ATLAS-QUANTUM

Hugging Face Space: Atlas-Quantum Space

Documentation: Hugging Face Docs

License

This model is licensed under the Apache 2.0 License. Please review the terms before use.

Metadata

The metadata block at the top ensures compatibility with Hugging Face's model card requirements. Replace placeholders (like ) with the appropriate information if available.

Changes Made

  1. Added YAML Metadata Block: This includes necessary fields such as library-name, tags, license, datasets, language, and model-specific information.
  2. Expanded README Content: Included an example for loading the model, clarified runtime issues, and improved formatting.
  3. Placeholders: Ensure to replace model-name and other placeholders with actual details.