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--- |
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language: |
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- es |
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tags: |
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- spanish |
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- sentiment |
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datasets: |
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- muchocine |
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widget: |
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- "Increíble pelicula. ¡Altamente recomendado!" |
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- "Extremadamente malo. Baja calidad" |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# electricidad-base-muchocine-finetuned |
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This model fine-tunes [mrm8488/electricidad-base-discriminator](https://huggingface.co/mrm8488/electricidad-base-discriminator) on [muchocine](https://huggingface.co/datasets/muchocine) dataset for sentiment classification to predict *star_rating*. |
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### How to use |
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The model can be used directly with the HuggingFace `pipeline`. |
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```python |
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from transformers import AutoTokenizer, AutoModelWithLMHead |
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tokenizer = AutoTokenizer.from_pretrained("shahp7575/gpt2-horoscopes") |
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model = AutoModelWithLMHead.from_pretrained("shahp7575/gpt2-horoscopes") |
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``` |
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### Examples |
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```python |
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from transformers import pipeline |
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clf = pipeline('sentiment-analysis', model=model, tokenizer=tokenizer) |
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clf('Esta película es una joya. Todo fue perfecto: historia, casting, dirección. Me encantó el clímax.') |
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>>> [{'label': '5', 'score': 0.9658033847808838}] |
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clf("La historia y el casting fueron geniales.") |
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>>> [{'label': '4', 'score': 0.6666394472122192}] |
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clf("Me gustó pero podría ser mejor.") |
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>>> [{'label': '3', 'score': 0.7013391852378845}] |
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clf("dinero tirado en esta pelicula") |
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>>> [{'label': '2', 'score': 0.7564149498939514}] |
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clf("esta película es una película absolutamente repugnante. odio todo al respecto. gastó tanto dinero.") |
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>>> [{'label': '1', 'score': 0.3040296733379364}] |
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``` |
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