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--- |
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language: es |
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tags: |
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- QA |
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- Q&A |
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datasets: |
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- BSC-TeMU/SQAC |
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widget: |
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- text: "question: ¿Cuál es el nombre que se le da a la unidad morfológica y funcional de los seres vivos? context: La célula (del latín cellula, diminutivo de cella, ‘celda’) es la unidad morfológica y funcional de todo ser vivo. De hecho, la célula es el elemento de menor tamaño que puede considerarse vivo.\u200b De este modo, puede clasificarse a los organismos vivos según el número de células que posean: si solo tienen una, se les denomina unicelulares (como pueden ser los protozoos o las bacterias, organismos microscópicos); si poseen más, se les llama pluricelulares. En estos últimos el número de células es variable: de unos pocos cientos, como en algunos nematodos, a cientos de billones (1014), como en el caso del ser humano. Las células suelen poseer un tamaño de 10 µm y una masa de 1 ng, si bien existen células mucho mayores." |
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--- |
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# Spanish T5 (small) fine-tuned on **SQAC** for Spanish **QA** 📖❓ |
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[spanish-T5-small](https://huggingface.co./flax-community/spanish-t5-small) fine-tuned on [SQAC](https://huggingface.co./datasets/BSC-TeMU/SQAC) for **Q&A** downstream task. |
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## Details of Spanish T5 (small) |
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T5 (small) like arch trained from scatch on [large_spanish_corpus](https://huggingface.co./datasets/large_spanish_corpus) for **HuggingFace/Flax/Jax Week**. |
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## Details of the dataset 📚 |
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This dataset contains 6,247 contexts and 18,817 questions with their answers, 1 to 5 for each fragment. |
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The sources of the contexts are: |
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* Encyclopedic articles from [Wikipedia in Spanish](https://es.wikipedia.org/), used under [CC-by-sa licence](https://creativecommons.org/licenses/by-sa/3.0/legalcode). |
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* News from [Wikinews in Spanish](https://es.wikinews.org/), used under [CC-by licence](https://creativecommons.org/licenses/by/2.5/). |
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* Text from the Spanish corpus [AnCora](http://clic.ub.edu/corpus/en), which is a mix from diferent newswire and literature sources, used under [CC-by licence](https://creativecommons.org/licenses/by/4.0/legalcode). |
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This dataset can be used to build extractive-QA. |
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## Results on test dataset 📝 |
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| Metric | # Value | |
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| ------ | --------- | |
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| **BLEU** | **41.94** | |
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## Model in Action 🚀 |
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```python |
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from transformers import T5ForConditionalGeneration, AutoTokenizer |
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import torch |
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device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') |
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ckpt = 'mrm8488/spanish-t5-small-sqac-for-qa' |
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tokenizer = AutoTokenizer.from_pretrained(ckpt) |
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model = T5ForConditionalGeneration.from_pretrained(ckpt).to(device) |
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def get_answer(question, context): |
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input_text = 'question: %s context: %s' % (question, context) |
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features = tokenizer([input_text ], padding='max_length', truncation=True, max_length=512, return_tensors='pt') |
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output = model.generate(input_ids=features['input_ids'].to(device), |
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attention_mask=features['attention_mask'].to(device)) |
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return tokenizer.decode(output[0], skip_special_tokens=True) |
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``` |
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> Created by [Manuel Romero/@mrm8488](https://twitter.com/mrm8488) | [LinkedIn](https://www.linkedin.com/in/manuel-romero-cs/) |
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> Made with <span style="color: #e25555;">♥</span> in Spain |
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