commit b650dc95df8b9754693b83e9c004395e2e2888ad
Author: ale <ale@debian>
Date:   Fri Jul 30 17:40:31 2021 +0200

    initial commit

diff --git a/README.md b/README.md
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+# MarIA la Biblioteca Nacional y el BSC crean un sistema especializado en el idioma español para mejorar las respuestas de las IA en nuestra lengua
+
+[https://www.xataka.com/robotica-e-ia/maria-biblioteca-nacional-bsc-crean-sistema-especializado-idioma-espanol-para-mejorar-respuestas-ia-nuestra-lengua](https://www.xataka.com/robotica-e-ia/maria-biblioteca-nacional-bsc-crean-sistema-especializado-idioma-espanol-para-mejorar-respuestas-ia-nuestra-lengua)
+
+[https://github.com/PlanTL-SANIDAD/lm-spanish](https://github.com/PlanTL-SANIDAD/lm-spanish)
+
+[https://huggingface.co/BSC-TeMU/roberta-large-bne](https://huggingface.co/BSC-TeMU/roberta-large-bne)
+
+```
+$ python3 roberta.py "la inteligencia <mask> es el presente"
+[' emocional', ' humana', ' no', ' artificial', ' colectiva']
+
+$ python3 roberta.py "la curiosidad <mask> al gato"
+[' mueve', ' mató', ' mata', ' ayuda', ' atrae']
+```
+
+## Build
+
+```
+docker-compose build
+
+or
+
+docker build -t maria ./maria
+```
+
+## Run
+
+```
+$ docker run --name maria --rm maria "hola <mask>, ¿qué tal?"
+[' guapa', ' chicas', ' amigos', ' chicos', ' amigo']
+```
+
+## License
+
+MIT
diff --git a/docker-compose.yml b/docker-compose.yml
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+version: '2'
+
+services:
+    maria:
+        build: ./maria
+        image: maria
+        hostname: maria
+        container_name: maria
+        restart: always
+        networks:
+            net:
+
+networks:
+  net:
+
diff --git a/maria/Dockerfile b/maria/Dockerfile
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+FROM python:3
+RUN curl https://sh.rustup.rs -sSf | sh -s -- -y
+RUN . /root/.cargo/env && pip3 install transformers torch flask
+RUN mkdir -p /maria
+WORKDIR /maria
+RUN git clone https://huggingface.co/BSC-TeMU/roberta-base-bne
+COPY ./roberta.py /maria/roberta.py
+RUN python3 roberta.py "hola <mask>"
+CMD "hola <mask>"
+ENTRYPOINT ["python3", "roberta.py"]
+
diff --git a/maria/roberta.py b/maria/roberta.py
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+from transformers import AutoModelForMaskedLM
+from transformers import AutoTokenizer, FillMaskPipeline
+from pprint import pprint
+import sys
+tokenizer_hf = AutoTokenizer.from_pretrained('BSC-TeMU/roberta-base-bne')
+model = AutoModelForMaskedLM.from_pretrained('BSC-TeMU/roberta-base-bne')
+model.eval()
+pipeline = FillMaskPipeline(model, tokenizer_hf)
+text = sys.argv[1:]
+res_hf = pipeline(text)
+pprint([r['token_str'] for r in res_hf])
+