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README.md

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 license: apache-2.0
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+# Unam_tesis_beto_finnetuning: Unam's thesis classification with BETO 
+
+
+This model is created from the finetuning of the pre-model
+for Spanish [BETO] (https://huggingface.co/dccuchile/bert-base-spanish-wwm-uncased), using PyTorch framework, 
+and trained with a set of theses at the Autonomous University of Mexico  [UNAM](https://tesiunam.dgb.unam.mx/F?func=find-b-0&local_base=TES01). 
+The model classifies for five (Psychology, Law, Química Farmaceutico Biológica, Actuaría, Economy) 
+possible careers at the University of Mexico.
+List of races from a text.
+
+
+## Example of use
+
+For further details on how to use unam_tesis_beto_finnetuning you can visit the Huggingface Transformers library, starting with the Quickstart section. Unam_tesis models can be accessed simply as 'inoid/unam_tesis_beto_finnetuning' by using the Transformers library. An example of how to download and use the models on this page can be found in this colab notebook. 
+```python
+
+ tokenizer = AutoTokenizer.from_pretrained('inoid/unam_tesis_beto_finnetuning', use_fast=False)
+ model = AutoModelForSequenceClassification.from_pretrained(
+                   'inoid/unam_tesis_beto_finnetuning', num_labels=5, output_attentions=False,
+                  output_hidden_states=False)
+ pipe = TextClassificationPipeline(model=model, tokenizer=tokenizer, return_all_scores=True)
+ 
+ classificationResult = pipe("El objetivo de esta tesis es elaborar un estudio de las condiciones asociadas al aprendizaje desde casa")
+
+```
+
+To cite this resource in a publication please use the following:
+
+
+## Citation
+
+[UNAM's Tesis with BETO finetuning classify ](https://users.dcc.uchile.cl/~jperez/papers/pml4dc2020.pdf)
+
+To cite this resource in a publication please use the following:
+
+```
+@inproceedings{SpanishNLPHackaton2022,
+  title={UNAM's Tesis with BETO finetunning classify },
+  author={Cañete, Isahías and López, Dionis and Clavel, Yisell},
+  booktitle={Somos NLP Hackaton 2022},
+  year={2022}
+}