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--- |
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license: apache-2.0 |
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language: |
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- ca |
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- es |
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- en |
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tags: |
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- RAG |
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pipeline_tag: text-generation |
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--- |
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# FLOR-6.3B Model optimized for QA |
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## Table of Contents |
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<details> |
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<summary>Click to expand</summary> |
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- [Model description](#model-description) |
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- [Intended uses and limitations](#intended-uses-and-limitations) |
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- [How to use](#how-to-use) |
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- [Limitations and bias](#limitations-and-bias) |
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- [Training](#training) |
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- [Evaluation](#evaluation) |
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- [Additional information](#additional-information) |
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</details> |
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## Model description |
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**FlorQARAG** is a 6.3B-parameter transformer-based causal language model for Catalan, Spanish, and English, trained on a customized QA dataset from various sources especifically to be used in RAG (Retrieval-Aumented Generation) Applications. |
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The dataset used to fine tune the model is: [PureInstructQA](https://huggingface.co/datasets/projecte-aina/PureInstructQA) |
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## Intended uses and limitations |
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The **FlorQARAG** model is ready-to-use for RAG applications optimized for Catalan language. |
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It can perform text-generation Question Answering in the context of RAG applications. |
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## How to use |
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```python |
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import torch |
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from transformers import pipeline |
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pipe = pipeline("text-generation", model="projecte-aina/FlorQARAG") |
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instruction = "Quants habitants té Mataró?" |
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context = "Mataró és una ciutat de Catalunya, capital de la comarca del Maresme. Situada al litoral mediterrani, a uns 30 km al nord-est de Barcelona, ha estat tradicionalment un centre administratiu de rellevància territorial i un pol de dinamisme econòmic. Compta amb prop de 130.000 habitants, essent actualment la vuitena població del Principat i la tretzena dels Països Catalans. " |
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# We need to format the prompt and context using ### and \n |
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def givePrediction(instruction, context, max_new_tokens=50, repetition_penalty=1.2, top_k=50, top_p=0.95, do_sample=True, temperature=0.5) |
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text = f"### Instruction\n{{instruction}}\n### Context\n{{context}}\n### Answer\n" |
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response = pipe(text.format(instruction=instruction, context=context),temperature=temperature,repetition_penalty=repetition_penalty, max_new_tokens=max_new_tokens,top_k=top_k, top_p=top_p, do_sample=do_sample)[0]["generated_text"] |
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answer = response.split("###")[-1][8:-1] |
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return answer |
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answer = givePrediction(instruction, context) |
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print(answer) |
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'130 000' |
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``` |
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## Limitations and bias |
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At the time of submission, no measures have been taken to estimate the bias and toxicity embedded in the model. |
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However, we are well aware that our models may be biased since the corpora have been collected using crawling techniques |
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on multiple web sources. We intend to conduct research in these areas in the future, and if completed, this model card will be updated. |
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## Training |
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### Instruction Data |
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The training corpus is composed of 82,539 QA instruction following examples. See Data Card at [PureInstructQA](https://huggingface.co/datasets/projecte-aina/PureInstructQA). |
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## Additional information |
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### Author |
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The Language Technologies Unit from Barcelona Supercomputing Center. |
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### Contact |
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For further information, please send an email to <[email protected]>. |
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### Copyright |
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Copyright(c) 2023 by Language Technologies Unit, Barcelona Supercomputing Center. |
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### License |
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[Apache License, Version 2.0](https://www.apache.org/licenses/LICENSE-2.0) |
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### Funding |
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This work was funded by [Departament de la Vicepresidència i de Polítiques Digitals i Territori de la Generalitat de Catalunya](https://politiquesdigitals.gencat.cat/ca/inici/index.html#googtrans(ca|en) within the framework of [Projecte AINA](https://politiquesdigitals.gencat.cat/ca/economia/catalonia-ai/aina). |
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### Disclaimer |
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<details> |
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<summary>Click to expand</summary> |
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The model published in this repository is intended for a generalist purpose and is available to third parties under a permissive Apache License, Version 2.0. |
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Be aware that the model may have biases and/or any other undesirable distortions. |
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When third parties deploy or provide systems and/or services to other parties using this model (or any system based on it) |
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or become users of the model, they should note that it is their responsibility to mitigate the risks arising from its use and, |
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in any event, to comply with applicable regulations, including regulations regarding the use of Artificial Intelligence. |
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In no event shall the owner and creator of the model (Barcelona Supercomputing Center) |
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be liable for any results arising from the use made by third parties. |
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</details> |
