language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- gemma
- trl
base_model: unsloth/gemma-2b-it-bnb-4bit
Uploaded model
- Developed by: rovi27, sbenel, GaboTuco, iXrst, andreamorgar
- Funded by: SomosNLP, HuggingFace
- Model type: Language model, instruction tuned
- Language(s):
es-CL,es-ES,es-MX,es-PE - License: apache-2.0
- Fine-tuned from model: https://huggingface.co/unsloth/gemma-2b-bnb-4bit
- Dataset used: [More Information Needed]
Model Sources
- Repository: https://github.com/recetasdelaabuela/somosnlp
- Paper: Comming soon!
- Demo: https://huggingface.co/spaces/somosnlp/ComeBien_Demo
- Video presentation: https://www.youtube.com/watch?v=WK-1F1TX5d4&list=PLTA-KAy8nxaASMwEUWkkTfMaDxWBxn-8J&index=19
This gemma model was trained 2x faster with Unsloth and Huggingface's TRL library.
More info in https://huggingface.co/datasets/somosnlp/RecetasDeLaAbuela
Uses
This models aims to provide a tool to improve healthy cooking habits.
Direct Use
Enhance recipes from Spanish-speaking countries with their nutritional values to help improve our relationship with food. The ultimate goal is to construct a Spanish-language specific intelligent nutrition assistant."
Out-of-Scope Use
This model will not work well for nutrititional needs from under-represented areas, as well as recipes in other languages rather than Spanish.
[More Information Needed]
Bias, Risks, and Limitations
This model has been trained using the data provided in the training dataset without the supervision of nutrition experts. Please use it wisely and always consider the recommendations and guidelines from international health foundations.
The model has been trained with recipes in Spanish from different areas of the world. Therefore, there can be biases regarding overrepresented areas, and some geographical areas may not be under-representation. We encourage the open-source community to collaborate in improving the dataset to cover as many geographic areas as possible!
Recommendations
Users should be made aware of the risks, biases and limitations of the model.
