Instructions to use iEsmeralda/mrm8488-finetuned-ner-tech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use iEsmeralda/mrm8488-finetuned-ner-tech with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="iEsmeralda/mrm8488-finetuned-ner-tech")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("iEsmeralda/mrm8488-finetuned-ner-tech") model = AutoModelForTokenClassification.from_pretrained("iEsmeralda/mrm8488-finetuned-ner-tech") - Notebooks
- Google Colab
- Kaggle
Model Description
Este modelo fue entrenado para reconocer entidades como "procesamiento de lenguaje natural" como una etiqueta TECH. Esto es útil debido a que el procesamiento de lenguaje natural reperesenta técnicas, y tiene más valor al ser reconocido como tal, que como palabras separadas como "procesamiento", "de", "lenguaje", "natural".
- Developed by: iEsmeralda
- Shared by: iEsmeralda
- Model type: Named Entity Recognition (NER)
- Language(s) (NLP): Spanish
- Finetuned from model: mrm8488/bert-spanish-cased-finetuned-ner
Model Sources
- Dataset: iEsmeralda/ner_tech_dataset_bio
How to Get Started with the Model
from transformers import AutoModelForTokenClassification, AutoTokenizer, pipeline
modelo = AutoModelForTokenClassification.from_pretrained("iEsmeralda/mrm8488-finetuned-ner-tech")
tokenizer = AutoTokenizer.from_pretrained("iEsmeralda/mrm8488-finetuned-ner-tech")
ner_pipeline = pipeline("ner", model=modelo, tokenizer=tokenizer, aggregation_strategy="simple")
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Model tree for iEsmeralda/mrm8488-finetuned-ner-tech
Base model
mrm8488/bert-spanish-cased-finetuned-ner