🚀 agrimi-7b-lora
agrimi-7b-lora is a chatbot-like model for dialogue generation. It was built by fine-tuning falcon-7B on the Greek translation of Alpaca dataset. This repo only includes the LoRA adapters from fine-tuning with 🤗's peft package.
Since, Greek language is not included in the pretrained falcon-7b model the performance of this model is not very good. The purpose of this model is mostly to demonstrate that even using a pretrained model without any knowledge of Greek language it is possible to utilize the global knowledge and apply transfer learning!
Model Details
Model Description
agrimi-7b-lora is a chatbot-like model for dialogue generation. It was built by fine-tuning falcon-7B on the Greek translation of Alpaca dataset. This repo only includes the LoRA adapters from fine-tuning with 🤗's peft package.
Since, Greek language is not included in the pretrained falcon-7b model the performance of this model is not very good. The purpose of this model is mostly to demonstrate that even using a pretrained model without any knowledge of Greek language it is possible to utilize the global knowledge and apply transfer learning!
- Developed by: More information needed
- Shared by [Optional]: More information needed
- Model type: Language model
- Language(s) (NLP): el
- License: apache-2.0
- Parent Model: More information needed
- Resources for more information: More information needed
Table of Contents
- Model Card for agrimi-7b-lora
- Table of Contents
- Table of Contents
- Model Details
- Uses
- Bias, Risks, and Limitations
- Training Details
- Evaluation
- Model Examination
- Environmental Impact
- Technical Specifications [optional]
- Citation
- Glossary [optional]
- More Information [optional]
- Model Card Authors [optional]
- Model Card Contact
- How to Get Started with the Model
Uses
Direct Use
Downstream Use [Optional]
Out-of-Scope Use
Bias, Risks, and Limitations
Significant research has explored bias and fairness issues with language models (see, e.g., Sheng et al. (2021) and Bender et al. (2021)). Predictions generated by the model may include disturbing and harmful stereotypes across protected classes; identity characteristics; and sensitive, social, and occupational groups.
Recommendations
Training Details
Training Data
More information on training data needed
Training Procedure
Preprocessing
More information needed
Speeds, Sizes, Times
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
Model Examination
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
Citation
BibTeX:
More information needed
APA:
More information needed
Glossary [optional]
More information needed
More Information [optional]
More information needed
Model Card Authors [optional]
Andreas Loupasakis
Model Card Contact
More information needed
How to Get Started with the Model
Use the code below to get started with the model.
Click to expand
More information needed
- Downloads last month
- 0