From 5ed70308a7f2713c0a20f6a0382280bb01ade0e1 Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Thu, 23 Apr 2026 20:14:07 +0800 Subject: [PATCH] =?UTF-8?q?=E5=88=9D=E5=A7=8B=E5=8C=96=E9=A1=B9=E7=9B=AE?= =?UTF-8?q?=EF=BC=8C=E7=94=B1ModelHub=20XC=E7=A4=BE=E5=8C=BA=E6=8F=90?= =?UTF-8?q?=E4=BE=9B=E6=A8=A1=E5=9E=8B?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Model: gplsi/Aitana-7B-S-base-1.0 Source: Original Platform --- .gitattributes | 36 ++++ README.md | 304 +++++++++++++++++++++++++++++++ config.json | 29 +++ generation_config.json | 6 + model-00001-of-00004.safetensors | 3 + model-00002-of-00004.safetensors | 3 + model-00003-of-00004.safetensors | 3 + model-00004-of-00004.safetensors | 3 + model.safetensors.index.json | 298 ++++++++++++++++++++++++++++++ special_tokens_map.json | 23 +++ tokenizer.json | 3 + tokenizer.model | 3 + tokenizer_config.json | 43 +++++ 13 files changed, 757 insertions(+) create mode 100644 .gitattributes create mode 100644 README.md create mode 100644 config.json create mode 100644 generation_config.json create mode 100644 model-00001-of-00004.safetensors create mode 100644 model-00002-of-00004.safetensors create mode 100644 model-00003-of-00004.safetensors create mode 100644 model-00004-of-00004.safetensors create mode 100644 model.safetensors.index.json create mode 100644 special_tokens_map.json create mode 100644 tokenizer.json create mode 100644 tokenizer.model create mode 100644 tokenizer_config.json diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..52373fe --- /dev/null +++ b/.gitattributes @@ -0,0 +1,36 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text +*.onnx filter=lfs diff=lfs merge=lfs -text +*.ot filter=lfs diff=lfs merge=lfs -text +*.parquet filter=lfs diff=lfs merge=lfs -text +*.pb filter=lfs diff=lfs merge=lfs -text +*.pickle filter=lfs diff=lfs merge=lfs -text +*.pkl filter=lfs diff=lfs merge=lfs -text +*.pt filter=lfs diff=lfs merge=lfs -text +*.pth filter=lfs diff=lfs merge=lfs -text +*.rar filter=lfs diff=lfs merge=lfs -text +*.safetensors filter=lfs diff=lfs merge=lfs -text +saved_model/**/* filter=lfs diff=lfs merge=lfs -text +*.tar.* filter=lfs diff=lfs merge=lfs -text +*.tar filter=lfs diff=lfs merge=lfs -text +*.tflite filter=lfs diff=lfs merge=lfs -text +*.tgz filter=lfs diff=lfs merge=lfs -text +*.wasm filter=lfs diff=lfs merge=lfs -text +*.xz filter=lfs diff=lfs merge=lfs -text +*.zip filter=lfs diff=lfs merge=lfs -text +*.zst filter=lfs diff=lfs merge=lfs -text +*tfevents* filter=lfs diff=lfs merge=lfs -text +tokenizer.json filter=lfs diff=lfs merge=lfs -text diff --git a/README.md b/README.md new file mode 100644 index 0000000..5d1b382 --- /dev/null +++ b/README.md @@ -0,0 +1,304 @@ +--- +license: apache-2.0 +language: + - ca + - es + - en +base_model: BSC-LT/salamandra-7b +tags: + - valencian + - catalan + - spanish + - english + - text-generation + - alia + - gplsi +datasets: + - gplsi/alia_dogv + - gplsi/alia_les_corts + - gplsi/alia_amic + - gplsi/alia_boua + - gplsi/alia_tourism +library_name: transformers +pipeline_tag: text-generation +--- + +# Aitana-7B-S-base-1.0 + +**Aitana-7B-S-base-1.0** is a generative language model from the **Aitana family**, developed by the [GPLSI (Language and Information System Group)](https://gplsi.dlsi.ua.es/) at the University of Alicante. This model is based on [BSC-LT/salamandra-7b](https://huggingface.co/BSC-LT/salamandra-7b) and has been continuously pre-trained on multilingual data (Valencian, Spanish, and English) to improve representation of Valencian and Catalan languages. + +## Table of Contents + +- [Model Description](#model-description) +- [Evaluation](#evaluation) +- [Training Data](#training-data) +- [Intended Uses](#intended-uses) +- [How to Use](#how-to-use) +- [Additional Information](#additional-information) + +## Model Description + +| Property | Value | +|----------|-------| +| **Base Model** | [BSC-LT/salamandra-7b](https://huggingface.co/BSC-LT/salamandra-7b) | +| **Architecture** | Transformer decoder-only | +| **Parameters** | ~7.77B | +| **Languages** | Valencian, Spanish, English | +| **License** | Apache 2.0 | + +Aitana-7B-S-base-1.0 extends the multilingual Salamandra foundation with additional training on domain-specific Valencian, Spanish, and English data. The training emphasizes administrative, legal, and tourism domains. + +## Training Data + +This model was trained on the following ALIA datasets: + +| Dataset ID | Name | Language | Source | +|------------|------|----------|--------| +| dc8 | dogv_va_2025 | Valencian | [gplsi/alia_dogv](https://huggingface.co/datasets/gplsi/alia_dogv) | +| dc9 | dogv_es_2025 | Spanish | [gplsi/alia_dogv](https://huggingface.co/datasets/gplsi/alia_dogv) | +| dc10 | corts_es_va_2025 | Spanish/Valencian | [gplsi/alia_les_corts](https://huggingface.co/datasets/gplsi/alia_les_corts) | +| dc11 | amic_va_2025 | Valencian | [gplsi/alia_amic](https://huggingface.co/datasets/gplsi/alia_amic) | +| dc12 | boua_va_2025 | Valencian | [gplsi/alia_boua](https://huggingface.co/datasets/gplsi/alia_boua) | +| dc13 | boua_es_2025 | Spanish | [gplsi/alia_boua](https://huggingface.co/datasets/gplsi/alia_boua) | +| dc14 | tourism_va_2025 | Valencian | [gplsi/alia_tourism](https://huggingface.co/datasets/gplsi/alia_tourism) | +| dc15 | tourism_es_2025 | Spanish | [gplsi/alia_tourism](https://huggingface.co/datasets/gplsi/alia_tourism) | +| dc16 | tourism_en_2025 | English | [gplsi/alia_tourism](https://huggingface.co/datasets/gplsi/alia_tourism) | + +### Data Sources + +- **DOGV (Diari Oficial de la Generalitat Valenciana)**: Official communications of the Valencian Community including laws and public sector communications +- **Les Corts Valencianes**: Transcripts from the Valencian Parliament plenary sessions and committee meetings +- **AMIC**: Valencian language corpus +- **BOUA (Butlletí Oficial de la Universitat d'Alacant)**: Official University of Alicante documents including grants, regulations, and resolutions +- **Tourism**: Multilingual tourism domain content + +## Intended Uses + +This model can be used for: + +- **Text generation** in Valencian, Spanish, and English +- **Fine-tuning** for specific downstream tasks +- **Domain adaptation** for administrative, legal, or tourism applications + +> **Note**: Due to the formal register of training data (administrative and legal domains), generated text tends toward formal language. + +## How to Use + +### Transformers + +```python +import torch +from transformers import pipeline, AutoTokenizer + +model_id = "gplsi/Aitana-7B-S-base-1.0" +tokenizer = AutoTokenizer.from_pretrained(model_id) + +generator = pipeline( + "text-generation", + model=model_id, + tokenizer=tokenizer, + torch_dtype=torch.bfloat16, + device_map="auto", +) + +# Valencian example +text = "Les corts valencianes han pres la decisió de" +result = generator(text, do_sample=True, top_k=10, max_new_tokens=100) +print(result[0]['generated_text']) + +# Spanish example +text = "El turismo en la Comunidad Valenciana" +result = generator(text, do_sample=True, top_k=10, max_new_tokens=100) +print(result[0]['generated_text']) +``` + + +## Evaluation + +In the following table, we can see the results obtained with different benchmarks from [lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness) in comparison with the model used for continuous pre-training. +The results have been obtained from the model pre-trained; no instruction tuning or fine-tuning of any kind has been performed. + +### Normalized score per language + +| Language | Salamandra-7B | Aitana-7B-S-base-1.0 | +|----------|----------|----------| +| **Spanish** | **0.255** | 0.252 | +| **Catalan** | 0.373 | **0.378** | +| **English** | 0.329 | **0.364** | +| **Valencian** | **0.614** | **0.614** | + +### Valencian + + +#### Classification Benchmarks + +| Dataset | Lang. | Task | Metric | Salamandra-7B | Aitana-7B-S-base-1.0 | +|------------------------------|--------|----------------------------|-------------|---------------|-----------------------| +| XNLI | va |Natural Language Inference | acc | **0.50** | 0.50 | + + +#### Generation Benchmarks + +| Dataset | Lang. | Task | Metric | Salamandra-7B | Aitana-7B-S-base-1.0 | +|------------------------------|--------|----------------------------|-------------|---------------|-----------------------| +| Cocoteros | va |Reading Comprehension | bleu | 12.01 | **16.19** | +| Phrases ca-va | va-ca |Translation - Adaptation | bleu | **86.80** | 85.33 | +| Phrases va-ca | va-ca |Translation - Adaptation | bleu | **94.71** | 80.00 | +| Phrases va-es | va-es |Translation | bleu | 79.74 | **80.59** | +| Phrases es-va | es-va |Translation | bleu | 66.42 | **69.78** | +| Truthfulqa_va | va | Truthfulness | bleu_acc| 0.33 | **0.37** | + + +### Catalan + + +#### Classification Benchmarks + +| Dataset | Lang. | Task | Metric | Salamandra-7B | Aitana-7B-S-base-1.0 | +|------------------------------|--------|----------------------------|-------------|---------------|-----------------------| +| Belebele Cat_latn | ca | Reading Comprehension | acc | 0.51 | **0.54** | +| COPA | ca | Commonsense Reasoning | acc | 0.80 | **0.82** | +| XStoryCloze | ca | Commonsense Reasoning | acc | 0.75 | **0.77** | +| OpenBookQA | ca | Question Answering | acc | 0.38 | **0.38** | +| PAWS | ca | Paraphrasing | acc | 0.62 | **0.62** | +| PiQA | ca | Question Answering | acc | 0.71 | **0.72** | +| SiQA | ca | Question Answering | acc | 0.49 | **0.51** | +| ARC Easy | ca | Question Answering | acc | 0.73 | **0.73** | +| ARC Challenge | ca | Question Answering | acc | **0.47** | 0.46 | +| XNLI | ca | Natural Language Inference | acc | **0.51** | 0.50 | +| Teca | ca | Natural Language Inference | acc | 0.53 | **0.53** | +| WNLI | ca | Natural Language Inference | acc | 0.59 | **0.62** | +| Catcola | ca | Linguistic Acceptability | acc | **0.73** | 0.73 | +| Catcola | ca | Linguistic Acceptability | mcc | **0.29** | 0.15 | +| Catalanqa | ca | Question Answering | F1 | 0.82 | **0.83** | +| Mgsm direct | ca | Math | exact match | 0.07 | **0.09** | +| Catalanqa | ca | Question Answering | exact match | 0.62 | **0.65** | +| Xquad | ca | Question Answering | exact match | 0.49 | **0.51** | +| Xquad | ca | Question Answering | F1 | 0.71 | **0.73** | + + + +#### Generation Benchmarks + +| Dataset | Lang. | Task | Metric | Salamandra-7B | Aitana-7B-S-base-1.0 | +|------------------------------|--------|----------------------------|--------|----------------|-----------------------| +| Cabreu abstractive | ca | Summarization | bleu | 8.73 | **11.32** | +| Cabreu extractive | ca | Summarization | bleu | **44.55** | 41.80 | +| Cabreu extreme | ca | Summarization | bleu | 10.66 | **12.54** | + + + +### Spanish + +#### Classification Benchmarks + +| Dataset | Lang. | Task | Metric | Salamandra-7B | Aitana-7B-S-base-1.0 | +|------------------------------|--------|---------------------------|-------------|---------------|-----------------------| +| Belebele | es | Reading Comprehension | acc | 0.493 | **0.561** | +| PAWS | es | Paraphrasing | acc | **0.608** | 0.591 | +| XNLI | es | Natural Language Inference| acc | **0.468** | 0.462 | +| WNLI | es | Natural Language Inference| acc | **0.465** | 0.437 | +| XStoryCloze | es | Commonsense Reasoning | acc | 0.745 | **0.756** | +| Escola | es | Linguistic Acceptability | acc | **0.706** | 0.678 | +| Escola | es | Linguistic Acceptability | mcc | **0.295** | 0.146 | +| OpenbookQA | es | Question Answering | acc | **0.406** | 0.382 | +| MGSM Direct | es | Math | exact match | 0.068 | **0.080** | +| XQUAD | es | Question Answering | exact match | 0.501 | **0.505** | +| XQUAD | es | Question Answering | F1 | 0.711 | **0.719** | + + + +#### Generation Benchmarks + +| Dataset | Lang. | Task | Metric | Salamandra-7B | Aitana-7B-S-base-1.0 | +|------------------------------|--------|---------------------|---------|----------------|-----------------------| +| Cocoteros | es |Reading Comprehension| bleu | 13.68 | **17.51** | +| XLSum | es | Summarization | bleu | 3.59 | **5.75** | + +### English + +#### Classification Benchmarks + +| Dataset | Lang. | Task | Metric | Salamandra-7B | Aitana-7B-S-base-1.0 | +|------------------------------|--------|----------------------------|-------------|---------------|-----------------------| +| Arc Challenge | en | Question Answering | acc | **0.527** | 0.526 | +| Arc Easy | en | Question Answering | acc | **0.824** | 0.814 | +| Belebele | en | Reading Comprehension | acc | 0.549 | **0.573** | +| PAWS | en | Paraphrasing | acc | **0.633** | 0.615 | +| XNLI | en | Natural Language Inference | acc | **0.483** | 0.476 | +| XStoryCloze | en | Commonsense Reasoning | acc | **0.795** | 0.793 | +| OpenBookQA | en | Question Answering | acc | 0.356 | **0.362** | +| PiQA | en | Question Answering | acc | 0.797 | **0.799** | +| Social iqa | en | Question Answering | acc | **0.513** | 0.512 | +| WNLI | en | Natural Language Inference | acc | 0.479 | **0.606** | +| MGSM Direct | en | Math | exact match | 0.280 | **0.564** | +| TriviaQA | en | Question Answering | exact match | 0.597 | **0.602** | +| CoLA | en | Linguistic Acceptability | mcc | **0.412** | 0.361 | + +## Additional Information + +### Author + +The model has been developed by the **Language and [Information Systems Group (GPLSI)](https://gplsi.dlsi.ua.es/)** and the **[Centro de Inteligencia Digital (CENID)](https://cenid.es)**, both part of the **[University of Alicante (UA)](https://www.ua.es/es/)**, as part of their ongoing research in **Natural Language Processing (NLP)**. + + +### Part of the Aitana Family + +This model is part of the Aitana model family developed by the GPLSI research group, which includes: + + - [gplsi/Aitana-2B-S](https://huggingface.co/gplsi/Aitana-2B-S) - Valencian-focused 2B model + - [gplsi/Aitana-2B-S-base-1.0](https://huggingface.co/gplsi/Aitana-2B-S-base-1.0) - Base version (1.0) of the 2B model + - [gplsi/Aitana-6.3B](https://huggingface.co/gplsi/Aitana-6.3B) - Larger 6.3B parameter model + - [gplsi/Aitana-TA-2B-S](https://huggingface.co/gplsi/Aitana-TA-2B-S) - Translation model (Spanish ↔ Valencian) + - [gplsi/Aitana-2B-S-LF](https://www.google.com/search?q=https://huggingface.co/gplsi/Aitana-2B-S-LF) - 2B Text Generation variant + - [gplsi/Aitana-2B-S-tourism-base-1.0](https://huggingface.co/gplsi/Aitana-2B-S-tourism-base-1.0) - Domain-specific base model focused on Tourism + - [gplsi/Aitana-tourism-mb-encoder-1.0](https://huggingface.co/gplsi/Aitana-tourism-mb-encoder-1.0) - Tourism domain Fill-Mask/Encoder model + - [gplsi/Aitana-FraudDetection-R-1.0](https://huggingface.co/gplsi/Aitana-FraudDetection-R-1.0) - Text Classification model for Fraud Detection + + +### Funding + +This work is funded by the **Ministerio para la Transformación Digital y de la Función Pública**, co-financed by the **EU – NextGenerationEU**, within the framework of the project *Desarrollo de Modelos ALIA*. + + +### Acknowledgments + +We would like to express our gratitude to all individuals and institutions that have contributed to the development of this work. + +Special thanks to: +- [Language Technologies Laboratory at Barcelona Supercomputing Center](https://www.bsc.es/es/discover-bsc/organisation/research-structure/language-technologies-laboratory) +- [Centro Vasco de Tecnología de la Lengua (HiTZ)](https://www.hitz.eus/es) +- [Centro Singular de Investigación en Tecnologías Inteligentes (CiTIUS)](https://citius.gal/) +- [Sistemas Inteligentes de Acceso a la Información (SINAI)](https://www.ujaen.es/investigacion-y-transferencia/grupos-de-investigacion/sistemas-inteligentes-de-acceso-la-informacion-sinai) +- [Instituto Universitario de Investigación Informática (IUII)](https://web.ua.es/es/iuii/) +- [Leonardo HPC System](https://leonardo-supercomputer.cineca.eu/) +- [European supercomputing ecosystem (EUROHPC)](https://www.eurohpc-ju.europa.eu/) + + +We also acknowledge the financial, technical, and scientific support of the **Ministerio para la Transformación Digital y de la Función Pública - Funded by EU – NextGenerationEU within the framework of the project Desarrollo de Modelos ALIA**, whose contribution has been essential to the completion of this research. + +### License + +[Apache License, Version 2.0](https://www.apache.org/licenses/LICENSE-2.0) + +### Disclaimer + +This model is intended for general purposes and is available under a permissive Apache License 2.0. Be aware that the model may have biases and/or undesirable outputs. Users deploying systems based on this model are responsible for mitigating risks and complying with applicable AI regulations. + +### Reference +```bibtex +@misc{gplsi-aitana-2B-S-base-1.0, + author = {Estevanell-Valladares, Ernesto L. and Yáñez-Romero, Fabio and Sepúlveda-Torres, Robiert and Consuegra-Ayala, Juan Pablo and Galiano, Santiago and Miró Maestre, María and Martínez-Murillo, Iván and Grande, Eduardo and Canal-Esteve, Miquel and Bonora, Mar and Gutierrez, Yoan and Abreu Salas, José Ignacio and Lloret, Elena and Montoyo, Andrés and Muñoz-Guillena and Palomar, Manuel}, + title = {Aitana 7B base: Continually pre-trained on Valencian}, + year = {2026}, + institution = {Language and Information Systems Group (GPLSI) and Centro de Inteligencia Digital (CENID), University of Alicante (UA)}, + howpublished = {\url{https://huggingface.co/gplsi/gplsi/Aitana-2B-S-base-1.0}}, + note = {Accessed: 2026-4-8} +} +``` + +--- + +**Copyright © 2026 Language and Information Systems Group (GPLSI) and Centro de Inteligencia Digital (CENID), +University of Alicante (UA). +Distributed under the Apache License 2.0.** diff --git a/config.json b/config.json new file mode 100644 index 0000000..340846f --- /dev/null +++ b/config.json @@ -0,0 +1,29 @@ +{ + "architectures": [ + "LlamaForCausalLM" + ], + "attention_bias": false, + "attention_dropout": 0.0, + "bos_token_id": 1, + "eos_token_id": 2, + "head_dim": 128, + "hidden_act": "silu", + "hidden_size": 4096, + "initializer_range": 0.02, + "intermediate_size": 11008, + "max_position_embeddings": 8192, + "mlp_bias": false, + "model_type": "llama", + "num_attention_heads": 32, + "num_hidden_layers": 32, + "num_key_value_heads": 8, + "pretraining_tp": 1, + "rms_norm_eps": 1e-05, + "rope_scaling": null, + "rope_theta": 10000.0, + "tie_word_embeddings": false, + "torch_dtype": "bfloat16", + "transformers_version": "4.40.2", + "use_cache": true, + "vocab_size": 256000 +} diff --git a/generation_config.json b/generation_config.json 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