Instructions to use xavierruth/spotify-pnl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xavierruth/spotify-pnl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="xavierruth/spotify-pnl")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("xavierruth/spotify-pnl") model = AutoModelForSequenceClassification.from_pretrained("xavierruth/spotify-pnl", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 432 Bytes
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license: mit
language:
- en
tags:
- sentiment-analysis
- bert
- transformers
metrics:
- bertscore
pipeline_tag: text-classification
library_name: transformers
model-index:
- name: spotify-pnl
results: []
---
# Modelo BERT para Análise de Sentimento de Reviews do Spotify
Este modelo foi treinado usando `AutoModelForSequenceClassification` do Hugging Face Transformers e está salvo no formato `safetensors`.
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