gemma-2-2b-ft-lora-noticias-es

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Lightweight finetuning of google/gemma-2-2b-it on a public dataset of news from Spanish digital newspapers (https://www.kaggle.com/datasets/josemamuiz/noticias-laraznpblico/).

Model Details

Model Description

This model is fine-tuned using LoRa (Low-Rank Adaptation) on the "Noticias La Razón y Público" dataset, a collection of Spanish news articles. The finetuning was done with lightweight methods to ensure efficient training while maintaining performance on the news-related language generation tasks.

• Developed by: https://talkingtochatbots.com
• Language(s) (NLP): Spanish (es)
• License: apache-2.0
• Finetuned from model: google/gemma-2-2b-it

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Uses

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Direct Use

This model can be used for conversational AI tasks related to Spanish-language news. The fine-tuned LoRa model is especially suitable for use cases that require both understanding and generating text, such as chat-based interactions, answering questions about news, and discussing headlines.

Copy the code from this Gist for easy chating using Jupyter Notebook: https://gist.github.com/reddgr/20c2e3ea205d1fedfdc8be94dc5c1237

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Bias, Risks, and Limitations

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Recommendations

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How to Get Started with the Model

Copy the code from this Gist for easy chating using Jupyter Notebook: https://gist.github.com/reddgr/20c2e3ea205d1fedfdc8be94dc5c1237

Additionally, you can use the code below to get started with the model.

!python from transformers import AutoTokenizer, AutoModelForCausalLM from peft import PeftModel

save_directory = "./fine_tuned_model" tokenizer = AutoTokenizer.from_pretrained(save_directory) model = AutoModelForCausalLM.from_pretrained(save_directory) peft_model = PeftModel.from_pretrained(model, save_directory)

input_text = "¿Qué opinas de las noticias recientes sobre la economía?" inputs = tokenizer(input_text, return_tensors="pt") output = peft_model.generate(**inputs, max_length=50) print(tokenizer.decode(output[0], skip_special_tokens=True))

Training Details

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Evaluation

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Testing Data, Factors & Metrics

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Summary

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Technical Specifications [optional]

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Framework versions

• PEFT 0.12.0