metadata

license: apache-2.0
datasets:
  - BAAI/Infinity-Instruct
  - HuggingFaceFW/fineweb
  - proj-persona/PersonaHub
  - sakharamg/AviationQA
  - danhoangg/AviationLLM
  - sakharamg/AviationCorpus
  - meghtedari/AviationRadio
  - jacobbieker/aeronet
  - OpenGVLab/ShareGPT-4o
  - kyle-lucke/planes
  - johnnydevriese/airplanes
  - AWeirdDev/airports
language:
  - en
  - fr
  - de
  - es
  - hi
  - ar
  - da
  - nl
  - ru
  - it
  - pt
  - id
  - cs
  - pl
metrics:
  - accuracy
library_name: adapter-transformers

Welcome to the new SkyReach Companion AI, created and developed by SkyX International Community.

This AI is specialised in aviation topic, and can help you with many queries.

Model Card for {{ model_id | default("Model ID", true) }}

This AI is specialised in aviation topic, and can help you with many queries.

Model Details

Model Description

The SkyReach Companion AI, developed by SkyX International Community, is part of the SkyReach Academy project. It answers a wide range of aviation-related questions and is continually improved to provide accurate and up-to-date information.

Developed by: {{ developers | default("[SkyX International Community]", true)}}
Funded by [optional]: {{ funded_by | default("[SkyX International Community]", true)}}
Shared by [optional]: {{ shared_by | default("[SkyX International Community]", true)}}
Model type: {{ model_type | default("[More Information Needed]", true)}}
Language(s) (NLP): {{ language | default("[en - fr - de - es - hi - ar - da - nl - ru - it - pt - id - cs - pl]", true)}}
License: {{ license | default("[Apache 2.0]", true)}}
Finetuned from model [optional]: {{ base_model | default("[More Information Needed]", true)}}

Model Sources [optional]

Repository: {{ repo | default("[https://huggingface.co/SkyXIntl/SkyReach_Companion_AI]", true)}}
Paper [optional]: {{ paper | default("[More Information Needed]", true)}}
Demo [optional]: {{ demo | default("[More Information Needed]", true)}}

Uses

Direct Use

{{ direct_use | default("[The model is used for answering aviation-related questions and generating content about aviation topics.]", true)}}

Downstream Use [optional]

{{ downstream_use | default("[It can be fine-tuned for specific aviation applications and integrated into aviation apps.]", true)}}

Out-of-Scope Use

{{ out_of_scope_use | default("[The model is not suitable for non-aviation-related queries or for tasks outside the scope of general aviation knowledge. It may not perform well with highly specialized or niche aviation topics not covered by its training data.]", true)}}

Bias, Risks, and Limitations

{{ bias_risks_limitations | default("[The model may reflect biases present in the training data. For instance, it might show bias towards certain airlines or geographical regions if the data is not balanced. Misinterpretation of the model’s responses may lead to incorrect aviation information being conveyed. The model’s accuracy is dependent on the quality and breadth of its training data. It may not always provide the most current or complete information.]", true)}}

Recommendations

{{ bias_recommendations | default("Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.", true)}}

How to Get Started with the Model

Use the code below to get started with the model.

{{ get_started_code | default("[More Information Needed]", true)}}

Training Details

Training Data

{{ training_data | default("[The model was trained using a diverse set of aviation-related datasets including flight data, aircraft specifications, and aviation texts. For detailed dataset information, refer to the Dataset Cards]", true)}}

Training Procedure

Preprocessing [optional]

Training Hyperparameters

Training regime: {{ training_regime | default("[More Information Needed]", true)}}

Speeds, Sizes, Times [optional]

{{ speeds_sizes_times | default("[More Information Needed]", true)}}

Evaluation

Testing Data, Factors & Metrics

Testing Data

Factors

{{ testing_factors | default("[More Information Needed]", true)}}

Metrics

{{ testing_metrics | default("[More Information Needed]", true)}}

Results

Summary

Model Examination [optional]

{{ model_examination | default("[More Information Needed]", true)}}

Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

Hardware Type: {{ hardware_type | default("[More Information Needed]", true)}}
Hours used: {{ hours_used | default("[More Information Needed]", true)}}
Cloud Provider: {{ cloud_provider | default("[More Information Needed]", true)}}
Compute Region: {{ cloud_region | default("[More Information Needed]", true)}}
Carbon Emitted: {{ co2_emitted | default("[More Information Needed]", true)}}

Technical Specifications [optional]

Model Architecture and Objective

Compute Infrastructure

{{ compute_infrastructure | default("[More Information Needed]", true)}}

Hardware

{{ hardware_requirements | default("[More Information Needed]", true)}}

Software

Citation [optional]

BibTeX:

{{ citation_bibtex | default("[More Information Needed]", true)}}

APA:

Glossary [optional]

More Information [optional]

{{ more_information | default("[More Information Needed]", true)}}

Model Card Authors [optional]

{{ model_card_authors | default("[More Information Needed]", true)}}

Model Card Contact

{{ model_card_contact | default("[More Information Needed]", true)}}