library_name: transformers
license: apache-2.0
pipeline_tag: text-generation
Model Details
Model Developers: Sogang University SGEconFinlab
Model Description
This model is a language model specialized in economics and finance. This was learned with various economic/finance-related data such as ํ๊ตญ์ํ ๊ฒฝ์ ์ฉ์ด, ๊ธ์ต์ฉ์ด์ฌ์ , KDI์์ฌ์ฉ์ด์ฌ์ , ํ๊ณ,์ธ๋ฌด์ฉ์ด์ฌ์ , ์ค์๊ธฐ์ ์ฒญ์ ๋ฌธ์ฉ์ด์ฌ์ , ํ๊ฒฝ๊ฒฝ์ ์ฉ์ด์ฌ์ , ๋งจํ๊ฒฝ์ ํ, TESAT ์์ฌ ์ฉ์ด ๋ฐ๋ผ์ก๊ธฐ, ๋งจํ๊ฒฝ์ ํ, ์๊ธ์๊ธ ํ๊ฒฝ, ์ค๋์ TESAT, ํ๊ฒฝ์ฃผ๋์ด TESAT. The data source is listed below, and since the data was used for research/policy purposes, we do not wish to disclose the trained data. If you wish to use it, please contact the original author for permission to use it.
- Developed by: Sogang University SGEconFinlab
- Model type: [More Information Needed]
- Language(s) (NLP): [More Information Needed]
- License: [More Information Needed]
- Base Model: yanolja/KoSOLAR-10.7B-v0.2
Model Sources [optional]
- Repository: [More Information Needed]
- Paper [optional]: [More Information Needed]
- Demo [optional]: [More Information Needed]
Uses
Direct Use
[More Information Needed]
[More Information Needed]
Out-of-Scope Use
[More Information Needed]
Bias, Risks, and Limitations
[More Information Needed]
Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
Training Details
Training Data
[More Information Needed]
Training Procedure
Preprocessing [optional]
[More Information Needed]
Training Hyperparameters
- Training regime: [More Information Needed]
Speeds, Sizes, Times [optional]
[More Information Needed]
Evaluation
Testing Data, Factors & Metrics
Testing Data
[More Information Needed]
Factors
[More Information Needed]
Metrics
[More Information Needed]
Results
[More Information Needed]
Summary
Model Examination [optional]
[More Information Needed]
Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- Hardware Type: [More Information Needed]
- Hours used: [More Information Needed]
- Cloud Provider: [More Information Needed]
- Compute Region: [More Information Needed]
- Carbon Emitted: [More Information Needed]
Technical Specifications [optional]
Model Architecture and Objective
[More Information Needed]
Compute Infrastructure
[More Information Needed]
Hardware
[More Information Needed]
Software
[More Information Needed]