Token Classification
Transformers
PyTorch
Enawené-Nawé
Trained with AutoTrain
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  language:
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  - unk
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- - text: "I love AutoTrain 🤗"
 
 
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  datasets:
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  - imranraad/autotrain-data-magpie-metaphor-xlmr
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  co2_eq_emissions:
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  emissions: 9.232131148683266
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  ---
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  # Model Trained Using AutoTrain
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  - Problem type: Entity Extraction
 
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  language:
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  - unk
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  widget:
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+ - text: "I’m sorry but I just can’t seem to wrap my head around it. - I’m sorry but I just can’t seem to understand."
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+ - text: "Why are you so bent out of shape? - Why are you so upset?"
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+ - text: "Listen, it is easier said than done, many people lack commitment."
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  datasets:
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  - imranraad/autotrain-data-magpie-metaphor-xlmr
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  co2_eq_emissions:
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  emissions: 9.232131148683266
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  ---
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+ # Fine-tune datasets
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+ - MAGPIE corpus: http://www.lrec-conf.org/proceedings/lrec2020/pdf/2020.lrec-1.35.pdf
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  # Model Trained Using AutoTrain
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  - Problem type: Entity Extraction