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README.md
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- unsloth
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- llama
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- trl
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language:
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- en
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---
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# Uploaded model
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- **License:** apache-2.0
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- **Finetuned from model :** unsloth/meta-llama-3.1-8b-bnb-4bit
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This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
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[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
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- unsloth
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- llama
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- trl
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- sft
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- tango
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license: llama3.1
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language:
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- en
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- es
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datasets:
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- spanish-ir/messirve
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- tatakof/messi_mod-v0.0.2
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pipeline_tag: text-generation
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library_name: transformers
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---
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# Uploaded model
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- **License:** apache-2.0
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- **Finetuned from model :** unsloth/meta-llama-3.1-8b-bnb-4bit
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## Evaluation Metrics
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|Task |Name |Description |Language|Metric |Task type |
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|--------------------------------------------------------------------------------------------------------|-------------------|-----------------------------------------------------------------------|--------|--------------|------------------------------------------|
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|[AQuAS](https://huggingface.co/datasets/IIC/AQuAS) |AQuAS |Abstractive Question-Answering in Spanish |ES |sas_encoder |Abstractive QA |
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|[ARC_ca](https://huggingface.co/datasets/projecte-aina/arc_ca) |ARC_ca |Grade-school level science questions in Catalan |CA |acc |Multi choice QA |
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|[BEC2016eu](https://huggingface.co/datasets/orai-nlp/basqueGLUE) |BEC2016eu |Basque Election Campaign 2016 Opinion Dataset |EU |f1 |Sentiment Analysis |
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|[Belebele Glg](https://huggingface.co/datasets/facebook/belebele) |Belebele Glg |Reading Comprehension in Galician |GL |acc |Reading Comprehension |
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|[BertaQA](https://huggingface.co/datasets/HiTZ/BertaQA) |BertaQA |Trivia dataset with global and local questions about the Basque Country|EU |acc |Multi choice QA |
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|[BHTCv2](https://huggingface.co/datasets/orai-nlp/basqueGLUE) |BHTCv2 |Topic Classification of News Headlines in Basque |EU |f1 |Classification, Topic Classification |
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|[caBREU](https://huggingface.co/datasets/projecte-aina/caBreu) |caBREU |Article Summarization in Catalan |CA |bleu |Summarization |
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|[CatalanQA](https://huggingface.co/datasets/projecte-aina/catalanqa) |CatalanQA |Extractive QA in Catalan |CA |f1 |Extractive QA |
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|[CatCoLA](https://huggingface.co/datasets/nbel/CatCoLA) |CatCoLA |Linguistic Acceptability in Catalan |CA |mcc |Linguistic Acceptability |
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|[ClinDiagnosES](https://huggingface.co/datasets/LenguajeNaturalAI/ClinDiagnosES) |ClinDiagnosES |Diagnosis of clinical cases in Spanish |ES |sas_encoder |Open QA |
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|[ClinTreatES](https://huggingface.co/datasets/LenguajeNaturalAI/ClinTreatES) |ClinTreatES |Treatment for clinical cases in Spanish |ES |sas_encoder |Open QA |
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|[COPA_ca](https://huggingface.co/datasets/projecte-aina/COPA-ca) |COPA_ca |Choice Of Plausible Alternatives in Catalan |CA |acc |Reasoning |
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|[CoQCat](https://huggingface.co/datasets/projecte-aina/CoQCat) |CoQCat |Conversational Question Answering in Catalan |CA |f1 |Extractive QA |
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|[Crows Pairs Spanish](https://huggingface.co/datasets/multilingual-crows-pairs/multilingual-crows-pairs)|Crows Pairs Spanish|Bias evaluation using stereotypes |ES |pct_stereotype|Bias Detection |
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|[EpecKorrefBin](https://huggingface.co/datasets/orai-nlp/basqueGLUE) |EpecKorrefBin |Coreference resolution in Basque |EU |acc |Coreference Resolution, Textual Entailment|
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|[EsCoLA](https://huggingface.co/datasets/nbel/EsCoLA) |EsCoLA |Spanish Corpus of Linguistic Acceptability |ES |mcc |Linguistic Acceptability |
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|[EusExams](https://huggingface.co/datasets/HiTZ/EusExams) |EusExams |Public Service examinations questions in Basque |EU |acc |Multi choice QA |
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|[EusProficiency](https://huggingface.co/datasets/HiTZ/EusProficiency) |EusProficiency |C1-level proficiency questions in Basque |EU |acc |Multi choice QA |
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|[EusReading](https://huggingface.co/datasets/HiTZ/EusReading) |EusReading |EGA exams reading comprehension in Basque |EU |acc |Multi choice QA |
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|[EusTrivia](https://huggingface.co/datasets/HiTZ/EusTrivia) |EusTrivia |Trivia questions in Basque |EU |acc |Multi choice QA |
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|[Fake News ES](https://huggingface.co/datasets/mariagrandury/fake_news_corpus_spanish) |Fake News ES |Fake News Detection in Spanish |ES |acc |Classification |
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|[GalCoLA](https://huggingface.co/datasets/proxectonos/galcola) |GalCoLA |Galician Corpus of Linguistic Acceptability |GL |mcc |Linguistic Acceptability |
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|[HumorQA](https://huggingface.co/datasets/LenguajeNaturalAI/HumorQA) |HumorQA |White humour joke classification |ES |acc |Classification |
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|[MGSM_ca](https://huggingface.co/datasets/projecte-aina/mgsm_ca) |MGSM_ca |Grade-school math problems in Catalan |CA |exact_match |Math Reasoning |
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|[MGSM_es](https://huggingface.co/datasets/juletxara/mgsm) |MGSM_es |Grade-school math problems in Spanish |ES |exact_match |Math Reasoning |
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|[MGSM_eu](https://huggingface.co/datasets/HiTZ/MGSM-eu) |MGSM_eu |Grade-school math problems in Basque |EU |exact_match |Math Reasoning |
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|[MGSM_gl](https://huggingface.co/datasets/proxectonos/mgsm_gl) |MGSM_gl |Grade-school math problems in Galician |GL |exact_match |Math Reasoning |
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|[NoticIA](https://huggingface.co/datasets/Iker/NoticIA) |NoticIA |A Clickbait Article Summarization Dataset in Spanish |ES |rouge1 |Summarization |
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|[OffendES](https://huggingface.co/datasets/SINAI/OffendES) |OffendES |Clasificación de comentarios ofensivos en español |ES |acc |Classification |
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|[OpenBookQA_ca](https://huggingface.co/datasets/projecte-aina/openbookqa_ca) |OpenBookQA_ca |Multi-step reasoning QA in Catalan |CA |acc |Reasoning |
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|[OpenBookQA_gl](https://huggingface.co/datasets/proxectonos/openbookqa_gl) |OpenBookQA_gl |Multi-step reasoning QA in Galician |GL |acc |Reasoning |
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|[Parafraseja](https://huggingface.co/datasets/projecte-aina/Parafraseja) |Parafraseja |Paraphrase identification in Catalan |CA |acc |Paraphrasing |
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|[ParafrasesGL](https://huggingface.co/datasets/proxectonos/parafrases_gl) |ParafrasesGL |Paraphrase identification in Galician |GL |acc |Paraphrasing |
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|[PAWS_ca](https://huggingface.co/datasets/projecte-aina/PAWS-ca) |PAWS_ca |Paraphrase Adversaries from Word Scrambling in Catalan |CA |acc |Paraphrasing |
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|[PAWS-X_es](https://huggingface.co/datasets/google-research-datasets/paws-x) |PAWS-X_es |Paraphrase Adversaries from Word Scrambling in Spanish |ES |acc |Paraphrasing |
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|[PAWS_gl](https://huggingface.co/datasets/proxectonos/PAWS-gl) |PAWS_gl |Paraphrase Adversaries from Word Scrambling in Galician |GL |acc |Paraphrasing |
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|[PIQA_ca](https://huggingface.co/datasets/projecte-aina/piqa_ca) |PIQA_ca |Physical Interaction QA in Catalan |CA |acc |Reasoning |
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|[QNLIeu](https://huggingface.co/datasets/orai-nlp/basqueGLUE) |QNLIeu |Textual Entailment in Basque |EU |acc |NLI, Textual Entailment |
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|[RagQuAS](https://huggingface.co/datasets/IIC/RagQuAS) |RagQuAS |Retrieval-Augmented-Generation and Question-Answering in Spanish |ES |sas_encoder |Abstractive QA |
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|[SIQA_ca](https://huggingface.co/datasets/projecte-aina/siqa_ca) |SIQA_ca |Social Interaction QA in Catalan |CA |acc |Reasoning |
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|[SpaLawEx](https://huggingface.co/datasets/LenguajeNaturalAI/examenes_abogacia) |SpaLawEx |Spanish Law School Access Exams |ES |acc |Multi choice QA |
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|[SummarizationGL](https://huggingface.co/datasets/proxectonos/summarization_gl) |SummarizationGL |Abstractive Summarization in Galician |GL |bleu |Summarization |
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|[TE-ca](https://huggingface.co/datasets/projecte-aina/teca) |TE-ca |Textual Entailment in Catalan |CA |acc |Textual Entailment |
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|[TELEIA](https://huggingface.co/datasets/gonzmart/teleia) |TELEIA |Test de Español como Lengua Extranjera para Inteligencia Artificial |ES |acc |Multi choice QA |
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|[VaxxStance](https://huggingface.co/datasets/orai-nlp/basqueGLUE) |VaxxStance |Stance detection on the Antivaxxers movement |EU |f1 |Sentiment Analysis, Stance Detection |
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|[WiCeu](https://huggingface.co/datasets/orai-nlp/basqueGLUE) |WiCeu |Word sense disambiguation in Basque |EU |acc |Textual Entailment |
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|[WNLI_ca](https://huggingface.co/datasets/projecte-aina/wnli-ca) |WNLI_ca |Winograd-schema-type dataset in Catalan |CA |acc |NLI, Textual Entailment |
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|[WNLI ES](huggingface.co/datasets/PlanTL-GOB-ES/wnli-es) |WNLI ES |Winograd-schema-type dataset in Spanish |ES |acc |NLI, Textual Entailment |
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|[XCOPA_eu](https://huggingface.co/datasets/HiTZ/XCOPA-eu) |XCOPA_eu |Choice Of Plausible Alternatives in Basque |EU |acc |Reasoning |
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|[XNLI_ca](https://huggingface.co/datasets/projecte-aina/xnli-ca) |XNLI_ca |Cross-lingual Natural Language Inference in Catalan |CA |acc |NLI, Textual Entailment |
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|[XNLI_es](https://huggingface.co/datasets/facebook/xnli) |XNLI_es |Cross-lingual Natural Language Inference in Spanish |ES |acc |NLI |
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|[XNLI_eu](https://huggingface.co/datasets/HiTZ/xnli-eu) |XNLI_eu |Cross-lingual Natural Language Inference in Basque |EU |acc |NLI, Textual Entailment |
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|[XQuAD_ca](https://huggingface.co/datasets/projecte-aina/xquad-ca) |XQuAD_ca |Cross-lingual Question Answering Dataset in Catalan |CA |f1 |Extractive QA |
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|[XQuAD_es](https://huggingface.co/datasets/google/xquad) |XQuAD_es |Cross-lingual Question Answering Dataset in Spanish |ES |f1 |Extractive QA |
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|[xStoryCloze_ca](https://huggingface.co/datasets/projecte-aina/xstorycloze_ca) |xStoryCloze_ca |Narrative completion in Catalan |CA |acc |Reasoning |
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|[xStoryCloze_es](https://huggingface.co/datasets/juletxara/xstory_cloze) |xStoryCloze_es |Narrative completion in Spanish |ES |acc |Reasoning |
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|[xStoryCloze_eu](https://huggingface.co/datasets/juletxara/xstory_cloze) |xStoryCloze_eu |Narrative completion in Basque |EU |acc |Reasoning |
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## Usage:
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You can use the model using HuggingFace Transformers library with 2 or more 80GB GPUs (NVIDIA Ampere or newer) with at least 150GB of free disk space to accomodate the download.
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This code has been tested on Transformers v4.44.0, torch v2.4.0 and 2 A100 80GB GPUs, but any setup that supports ```meta-llama/Llama-3.1-70B-Instruct``` should support this model as well. If you run into problems, you can consider doing ```pip install -U transformers```.
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```python
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# Use a pipeline as a high-level helper
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from transformers import pipeline
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pipe = pipeline("text-generation", model="sandbox-ai/Llama-3.1-Tango-8b-f16")
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```
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## References(s):
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* TODO
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## Model Architecture:
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**Architecture Type:** Transformer <br>
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**Network Architecture:** Llama 3.1 <br>
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## Input:
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**Input Type(s):** Text <br>
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**Input Format:** String <br>
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**Input Parameters:** One Dimensional (1D) <br>
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**Other Properties Related to Input:** Max of 128k tokens<br>
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## Output:
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**Output Type(s):** Text <br>
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**Output Format:** String <br>
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**Output Parameters:** One Dimensional (1D) <br>
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**Other Properties Related to Output:** Max of 4k tokens <br>
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# Training & Evaluation:
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- TODO
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# Dataset:
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**MessIRve: A Large-Scale Spanish Information Retrieval Dataset** <br>
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* [spanish/-ir/messirve](https://huggingface.co/datasets/spanish-ir/messirve) <br>
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** messi_mod-v0.0.2
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[tatakof/messi_mod-v0.0.2](https://huggingface.co/datasets/tatakof/messi_mod-v0.0.2)
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## Citation
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```bibtex
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@article{valentini2024messirve,
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title={MessIRve: A Large-Scale Spanish Information Retrieval Dataset},
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author={Francisco Valentini and Viviana Cotik and Damián Furman and Ivan Bercovich and Edgar Altszyler and Juan Manuel Pérez},
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year={2024},
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eprint={2409.05994},
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journal={arxiv:2409.05994},
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archivePrefix={arXiv},
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primaryClass={cs.CL},
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url={https://arxiv.org/abs/2409.05994},
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}
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@misc{wang2024helpsteer2preferencecomplementingratingspreferences,
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title={HelpSteer2-Preference: Complementing Ratings with Preferences},
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author={Zhilin Wang and Alexander Bukharin and Olivier Delalleau and Daniel Egert and Gerald Shen and Jiaqi Zeng and Oleksii Kuchaiev and Yi Dong},
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year={2024},
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eprint={2410.01257},
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archivePrefix={arXiv},
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primaryClass={cs.LG},
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url={https://arxiv.org/abs/2410.01257},
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}
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This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
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[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
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