|
--- |
|
license: apache-2.0 |
|
language: |
|
- ko |
|
library_name: transformers |
|
--- |
|
# Model Details |
|
|
|
 |
|
|
|
## Model Description |
|
|
|
<!-- Provide a longer summary of what this model is/does. --> |
|
POLAR is a Korean LLM developed by Plateer's AI-lab. It was inspired by Upstage's SOLAR. We will continue to evolve this model and hope to contribute to the Korean LLM ecosystem. |
|
|
|
- **Developed by:** AI-Lab of Plateer(Woomun Jung, Eunsoo Ha, MinYoung Joo, Seongjun Son) |
|
- **Model type:** Language model |
|
- **Language(s) (NLP):** ko |
|
- **License:** apache-2.0 |
|
- Parent Model: x2bee/POLAR-14B-v0.2 |
|
|
|
|
|
|
|
# Uses |
|
|
|
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> |
|
|
|
## Direct Use |
|
``` |
|
from transformers import AutoTokenizer, AutoModelForCausalLM |
|
|
|
tokenizer = AutoTokenizer.from_pretrained("x2bee/POLAR-7B-SFT-V1.0") |
|
model = AutoModelForCausalLM.from_pretrained("x2bee/POLAR-7B-SFT-V1.0") |
|
``` |
|
|
|
|
|
## Downstream Use [Optional] |
|
|
|
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> |
|
<!-- If the user enters content, print that. If not, but they enter a task in the list, use that. If neither, say "more info needed." --> |
|
|
|
|
|
|
|
|
|
## Out-of-Scope Use |
|
|
|
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> |
|
<!-- If the user enters content, print that. If not, but they enter a task in the list, use that. If neither, say "more info needed." --> |
|
|
|
|
|
|
|
|
|
# Bias, Risks, and Limitations |
|
|
|
<!-- This section is meant to convey both technical and sociotechnical limitations. --> |
|
|
|
Significant research has explored bias and fairness issues with language models (see, e.g., [Sheng et al. (2021)](https://aclanthology.org/2021.acl-long.330.pdf) and [Bender et al. (2021)](https://dl.acm.org/doi/pdf/10.1145/3442188.3445922)). Predictions generated by the model may include disturbing and harmful stereotypes across protected classes; identity characteristics; and sensitive, social, and occupational groups. |
|
|
|
|
|
## Recommendations |
|
|
|
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> |
|
|
|
|
|
|
|
|
|
|
|
# Training Details |
|
|
|
## Training Data |
|
|
|
<!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> |
|
|
|
More information on training data needed |
|
|
|
|
|
## Training Procedure |
|
|
|
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> |
|
|
|
### Preprocessing |
|
|
|
More information needed |
|
|
|
### Speeds, Sizes, Times |
|
|
|
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> |
|
|
|
More information needed |
|
|
|
# Evaluation |
|
|
|
<!-- This section describes the evaluation protocols and provides the results. --> |
|
|
|
## Testing Data, Factors & Metrics |
|
|
|
### Testing Data |
|
|
|
<!-- This should link to a Data Card if possible. --> |
|
|
|
More information needed |
|
|
|
|
|
### Factors |
|
|
|
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> |
|
|
|
More information needed |
|
|
|
### Metrics |
|
|
|
<!-- These are the evaluation metrics being used, ideally with a description of why. --> |
|
|
|
More information needed |
|
|
|
## Results |
|
|
|
More information needed |
|
|
|
# Model Examination |
|
|
|
More information needed |
|
|
|
# Environmental Impact |
|
|
|
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> |
|
|
|
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). |
|
|
|
- **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 |
|
|
|
# Citation |
|
|
|
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> |
|
|
|
**BibTeX:** |
|
|
|
More information needed |
|
|
|
**APA:** |
|
|
|
More information needed |
|
|
|
# Glossary [optional] |
|
|
|
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> |
|
|
|
More information needed |
|
|
|
# More Information [optional] |
|
|
|
If you would like more information about our company, please visit the link below. |
|
[tech.x2bee.com](https://tech.x2bee.com/) |
|
|
|
|
|
# Model Card Authors [optional] |
|
|
|
<!-- This section provides another layer of transparency and accountability. Whose views is this model card representing? How many voices were included in its construction? Etc. --> |
|
|
|
Woomun Jung, MinYoung Joo, Eunsu Ha, Seungjun Son |
|
|
|
# Model Card Contact |
|
|
|
More information needed |
|
|
|
# How to Get Started with the Model |
|
|
|
Use the code below to get started with the model. |
|
|
|
<details> |
|
<summary> Click to expand </summary> |
|
|
|
More information needed |
|
|
|
</details> |
